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rafstahelin/AI Toolkit-helpme.txt

Last active August 17, 2024 11:55
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AI Toolkit-helpme.txt
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"content": "Hi guys, I'm pretty new on this and seems like theres lots of stuff, why dont make a step by step guide and pretty much cut lots of questions",
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"description": "Uploaded a walkthrough of how to set up @ostrisai AI Toolkit training script for @bfl_ml 's Flux Dev! (Link in Thread)\n\nI was successful in running it locally, and wanted to give others a quick guide to how to set it up.\n\nApologies for the quality, I was trying to get it out",
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"content": "The readme on the GitHub is pretty step by step",
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"content": "I'm getting this error: found unknown escape character 'd'\n in \"<unicode string>\", line 30, column 50:\n ... path: \"E:\\training 3\\ai-toolkit\\datasets\\mia\"\n\nI've tried reinstalling several times and still getting the same issue",
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"content": "`path: \"E:\\\\training 3\\\\ai-toolkit\\\\datasets\\\\mia\"`\n@lightnlense",
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"content": "Hey trying to do my first Lora with flux getting this error, any ideas? 4090/WSL with Anaconda. Also is \"loading transformer\" part normal to take like 5 mins before it moves",
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"content": "/mnt/d/ai-toolkit/training/elon/18.png seem to be the issue will try to delete and try again...",
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"content": "maybe currupted image",
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"content": "I deleted the \"18.png\" no error and it looked like it was working...but then bam \"killed\"",
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"content": "with no reason",
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"content": "Generally if it says killed it is because your OS killed it because you afre out of CPU ram. You probably need at least 48gb of ram to handle training flux. Do you have less than that?",
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"content": "Yeah I got 32GB :/",
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"content": "and 24GB VRAM",
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"content": "I will try to optomize it for less ram if I can. I have had others contact me with 32 running into the same problem. I couldnt find a solution unfortunatly.",
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"content": "Oh no worries. Thanks",
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"content": "I might actually have extra RAM stick lying around might try it...",
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"content": "is that specifically for wsl? ai-toolkit works fine for me on 32gb ram and 24gbvram",
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"content": "Really. Interesting. How much ram is it using?",
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"content": "max vram and erh.. i think only like 20 or less of ram",
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"content": "I run it with 24gb vram and 16gb ram",
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"content": "prob maxes out but got some loras trained lol",
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"content": "I think it runs out of ran during quantization. It you do low_vrama, it quantizes on the cpu, which takes about 24gb of ram. Otherise, it runs on the gpu and wiht same requirements",
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"content": "Is there a number of images for a training Lora with Flux that's considered the sweet spot and not to go too much over? I just tried my first training using a formatted dataset of 150 images that worked great for an XL Lora, but after 1000 steps with that, the build and hairstyle look accurate, but the face and skin tone constantly look like diffferent people. Do I need to cut down on the image count or up the step count?",
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"content": "I might also just try one with a smaller dataset. This first one was an HD live action person with 150 images, but I just pulled off training XL and Pony sets of an anime character using CivitAI's trainer+presets and just 31 images",
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"content": "Thank you for the great tool and your work! I have made several Lora, when testing during training the results are as expected, but in Comfi the work does not meet expectations. On what workflow do you check the work of Lora? Maybe I have the wrong connection?",
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"content": "This has been mentioned before ..... first update comfy ........ and i use the lora stacker to load the lora \uD83D\uDE09",
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"content": "Hey heroes, currently stuck on this error, any ideas?\n\nError running job: [WinError 126] The specified module could not be found. Error loading \"D:\\Flux AI Toolkit\\ai-toolkit\\venv\\Lib\\site-packages\\torch\\lib\\fbgemm.dll\" or one of its dependencies.",
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"content": "Hi there yes i had this too",
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"content": "i had to manually add it. I googled for the same error and there is file you can download and insert into the location... after that it works. @Ostris including you as this seems to be an intermittent install error on windows 11",
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"content": "You on Linux?",
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"content": "It´s taking ages for each sample on my 4080 Nvidia with 32 gb Vram.. would really appreciate some advice",
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"content": "@Ostris Small request on start and running AI_Toolkit on runpod \uD83D\uDE4C \nOr may be redirect on some already available guide\\tutorial...",
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"content": "good morning folks",
"author": {
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"content": "qq, how do you know when your lora is over cooked?\nif it when it strats to produce images close to the training dataset and nothing else?",
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"content": "like if it takes on even the style or details it shouldn't",
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"content": "awesome, thank you",
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"content": "anecdotal but i was trying to train a \"t-pose\" pose lora and after a while it would take on the subtle shading and artstyle of the dataset which i didn't want",
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"content": "omg..thanks, the error was driving me crazy",
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"content": "> Running 1 job\n> Error running job: [WinError 126]. Error loading \"D:\\AI\\AI-trainer\\ai-toolkit\\venv\\lib\\site-packages\\torch\\lib\\fbgemm.dll\" or one of its dependencies.",
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"content": "any ideas why this could happen? the files are in place",
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"content": "This is a torch bug on windows. There are some solutions here, but looks like the next release of torch will have it fixed https://discuss.pytorch.org/t/failed-to-import-pytorch-fbgemm-dll-or-one-of-its-dependencies-is-missing/201969/59",
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"content": "sad:/ \nthanks.",
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"content": "Working fine on conda windows 11...so far",
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"content": "generally after how many steps is everyone saving their loras?\n200 steps, 500?",
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"content": "250 is default, I guess it's up to you",
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"content": "thanks, asking in order to try to not miss out of the lora steps sweet spot \uD83D\uDE42",
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"content": "Will the lora output work straight in comfyui? I've read something about converting the lora for comfyui....nvm it works out the box",
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"content": "Hey! I have this error when I change the batch size\nError running job: The size of tensor a (72) must match the size of tensor b (2) at non-singleton dimension 3\n\nAnyone knows why ?",
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"content": "I used this approach to fix it",
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"content": "I train on 24gbs 4090 just fine, trying to do inference on a 12gb 4070 on comfyui. I can infer on the fp8 dev on this card but the moment i add a lora it crashes comfy.\n\nAnyone loaded a lora on 12gb in comfy?",
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"content": "no sorry, its very vram intensive",
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"content": "i offload some of the nodes to my A4000 and let the model run on the A5000,",
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"content": "hi everyone \ni have a question\n\ncan i use the flux dev .safetensors file that i already have for training instead of downloading the model again? \ni have a very bad internet connection, that would take long for me and it could stop midway with no ability to resume it",
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"content": "im pretty sure it uses the diffusers version so no",
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"content": "is there a way to transform the safetensors one to the diffusers one?",
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"content": "have the same. Just use first day commit instead of latest and batch works fine (but probably have other already fixed bugs)",
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"content": "Hello, I have an RTX 4080 Super and I can run Flux Schnell, but when combined with Lora, it becomes very slow. This also applies to flux1-dev-fp8.",
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"content": "Shouldn't it work with the 11GB model?",
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"content": "My images have 4:5 aspect ratio—should I stick sdxl 1mpixel at like 896x1152?",
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"content": "hi",
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"content": "Training failed.\n\nCommand '['python', 'run.py', 'config/replicate.yml']' returned non-zero exit status 1.",
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"content": "@Ostris whats the current wisdom on pushing the mpixel size of the dataset images. On one side I’ve understood flux is very sensitive about aspect ratios. Could I change the resolutions to 1152 on the top end?",
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"content": "Flux handle aspect ratios very well from my experience. The Rotart positional encoder is fantastic. You will probably have aspect issues if you train layers in it, but ai-toolkit doesnt touch those layers so it should be fine.",
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"content": "optimizer.pt <- what is the purpose of this lora file when the training finishes?",
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"content": "its the file that lets you resume",
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"content": "Anyone know why I get this error? expected escape sequence of 8 hexadecimal numbers, but found 's'",
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"content": "the only time i seen a escape sequence error was related to a \\ without a \\\\ in the input folder",
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"content": "Hello \uD83D\uDC4B \n\nA bit of a noob question, but after training a LoRa, how does one apply it to generate more images?",
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"content": "comfyui load lora in your workflow",
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"content": "i haven't really used confyui before, \ni'm guessing there's no script that i can run? tried one from those guys but i think there's some incompatibility https://github.com/XLabs-AI/x-flux as it crashes when loading",
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"content": "probably your vram",
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"content": "i can load fp8 on 12gb but it almost always crashes if i try a lora",
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"content": "i can load any version of dev i want + lora on 24gb vram tho",
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"content": "running a 4090, so not vram related, there's some torch issue \n```\nTypeError: empty() received an invalid combination of arguments - got (tuple, dtype=NoneType, device=NoneType), but expected one of:\n * (tuple of ints size, *, tuple of names names, torch.memory_format memory_format = None, torch.dtype dtype = None, torch.layout layout = None, torch.device device = None, bool pin_memory = False, bool requires_grad = False)\n * (tuple of ints size, *, torch.memory_format memory_format = None, Tensor out = None, torch.dtype dtype = None, torch.layout layout = None, torch.device device = None, bool pin_memory = False, bool requires_grad = False)\n```",
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"content": "seamns like the ckpts work with https://replicate.com/lucataco/flux-dev-lora but it's kinda limting that you can't use private repos & you can't choose the file",
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"content": "@Ostris getting this error\n\n File \"/home/Ubuntu/Documents/ai-toolkit/run.py\", line 90, in <module>\n main()\n File \"/home/Ubuntu/Documents/ai-toolkit/run.py\", line 86, in main\n raise e\n File \"/home/Ubuntu/Documents/ai-toolkit/run.py\", line 78, in main\n job.run()\n File \"/home/Ubuntu/Documents/ai-toolkit/jobs/ExtensionJob.py\", line 22, in run\n process.run()\n File \"/home/Ubuntu/Documents/ai-toolkit/jobs/process/BaseSDTrainProcess.py\", line 1701, in run\n loss_dict = self.hook_train_loop(batch)\n File \"/home/Ubuntu/Documents/ai-toolkit/extensions_built_in/sd_trainer/SDTrainer.py\", line 1493, in hook_train_loop\n loss = self.calculate_loss(\n File \"/home/Ubuntu/Documents/ai-toolkit/extensions_built_in/sd_trainer/SDTrainer.py\", line 434, in calculate_loss\n loss = apply_snr_weight(loss, timesteps, self.sd.noise_scheduler, self.train_config.min_snr_gamma)\n File \"/home/Ubuntu/Documents/ai-toolkit/toolkit/train_tools.py\", line 733, in apply_snr_weight\n all_snr = get_all_snr(noise_scheduler, loss.device)\n File \"/home/Ubuntu/Documents/ai-toolkit/toolkit/train_tools.py\", line 652, in get_all_snr\n alphas_cumprod = noise_scheduler.alphas_cumprod\n File \"/home/Ubuntu/Documents/ai-toolkit/venv/lib/python3.10/site-packages/diffusers/configuration_utils.py\", line 143, in __getattr__\n raise AttributeError(f\"'{type(self).__name__}' object has no attribute '{name}'\")\nAttributeError: 'CustomFlowMatchEulerDiscreteScheduler' object has no attribute 'alphas_cumprod'",
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"content": "now im getting this Error running job: No module named 'ipadapter.ip_adapter'",
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"content": "If you're on Linux, make sure to run `git submodule update --init --recursive` (from the README)",
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"content": "windows unfortunately",
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"content": "These are Windows instructions from the README, looks like you also have to run the `git submodule update`",
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"content": "Has nothing to do with your config/yaml, just make sure you get the submodules",
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"content": "So i get this when I try to run that submodule: fork: Resource temporarily unavailable",
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"content": "ahhh. Then this was my issue. I saw that error when I installed. Thank you sir. I will try again in a bit.",
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"content": "@Ostris does this being set to false imply captioning does nothing?",
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"content": "or does it mean that captions still pass through the text encoder to influence the model, but the encoder itself doesn't receive any training (TL:DR captions do something)",
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"content": "Based on actual training outcomes. No it doesn’t. Captions are used.",
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"content": "@Ostris I have now tried every variation of settings and hyperparameters imaginable to fix this issue of training ooming slowing down stopping after x amount of steps. please let me know when you take a look at the code for windows if theres a bug related to this, thanks. if you can't take a look at it because you busy just let me know , ill install Linux and give that a try. thanks.",
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"content": "You should try it on runpod",
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"content": "Hi! I made a fork of AI-Toolkit to train my own LORA in Google Colab and it worked well, thank you! The sample images are really good and I got my safetensor.\n\nI made a colab for FLUX1.dev ( https://colab.research.google.com/drive/1kcIpNZ5IHPfEQBgqTErHwK6dER7SJhnl?usp=sharing ) and I'd like to implement a LORA option with a:\n\nuse_lora = True #@param {type:\"boolean\"}\nlora_path = \"/content/drive/MyDrive/LORA/my_first_flux_lora_v1.safetensors\" #@param {type:\"string\"}\nlora_strength = 0.9 #@param {type:\"slider\", min:0.0, max:1.0, step:0.1}\n\nBut if images are made, there's no trace of my LORA in the results.\n\nMy question is, could you give me a simple Python way to use a LORA with Flux. I need something like this, but with LORA:\n\nimport torch\nfrom diffusers import FluxPipeline\n\npipe = FluxPipeline.from_pretrained(\"black-forest-labs/FLUX.1-dev\", torch_dtype=torch.bfloat16)\npipe.enable_model_cpu_offload() \n\nprompt = \"A cat holding a sign that says hello world\"\nimage = pipe(\n prompt,\n height=1024,\n width=1024,\n guidance_scale=3.5,\n num_inference_steps=50,\n max_sequence_length=512,\n generator=torch.Generator(\"cpu\").manual_seed(0)\n).images[0]\nimage.save(\"flux-dev.png\")",
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"content": "So I trained a single person on about 20 to 30 images. How do I get around the problem when I want other people in the scene they only look or resemble the trained person? So far I've tried 2000 steps",
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"content": "ive trained a flux lora, it looks perfect in the samples images thats been generated while trained- but I cant make it work at comfyui. how to make it work at comfyui?",
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"content": "give me an example of the scene you are creating please",
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"content": "This is a common question, you need to ensure you are using the exact save tensor that aligns to the sample output... learning means the model can go back and forward in convergence.",
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"content": "Yes, the latter. it means that the text encoder is frozen but its output are still used to help the network and train it's interpretation of it. Flux use the T5 text encoder which might be too large for training lora on it, and as noted by the comment, it's currently untested. \nThere is two aspects of flux that makes it less necessary to train the text encoders:\n* since T5 was trained on text and not text-image pairs like CLIP, prompt embeds from T5 are more generic,\n* flux is large enough to revise it's interpretation of the prompt embeds.",
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"content": "guys, some help? please, i have instaled cuda, python -c \"import torch; x = (torch.cuda.get_device_name(0) if torch.cuda.is_available() else None); print(x)\"\nNVIDIA GeForce RTX 4090 , but when i run ai toolkit i get this message: UserWarning: torch.cuda.amp.GradScaler is enabled, but CUDA is not available. Disabling. , and starting to train but my gpu is not used, what is the problem?",
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"content": "the version of pytorch you have installed might not have cuda support: ```bash\ncd ai-toolkit\nsource venv/bin/activate\n# Shows the current pytorch version, should end with something like +cu124:\npython -c 'import torch; print(torch.__version__)'\n# Installs cuda enabled version\npip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124\n``` For the install command, see here: <https://pytorch.org/get-started/locally/>",
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"content": "i have unistaled torch torchvision torchaudio and reinstaled them and now working, tnx",
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"content": "are you folowing the guide on the github?",
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"content": "yap, Is it normal for generating the first 10 images to take this long? I've been waiting for 40 minutes and it has only generated one.",
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"content": "no, it's not normal... on a 4090... try disabling the first samples (skip_first_sample: true) to see how the training goes for you (if there are other problems)",
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"content": "i have restarted training and now is working good",
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"content": "git submodule update --init --recursive when trying to do this git submodule update --init --recursive",
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"content": "anyone know why?",
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"content": "uhmm I didn't understand",
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"content": "In the windows instructions",
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"content": "when I do this command . git submodule update --init --recursive",
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"content": "sorry thats the error. Its too early lol",
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"content": "I got this problem",
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"content": "someone said my error might be due to git being down but I doubt it. anyone have any suggestions?",
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"timestamp": "2024-08-15T15:08:04.997+02:00",
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"content": "Try removing the folder where you had the repo",
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"content": "And git clone from scratch",
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"content": "thanks I'll try that.",
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"content": "@obsdC:/Program Files/Git/mingw64/libexec/git-core\\git-submodule: fork: Resource temporarily unavailable",
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"content": "same error",
"author": {
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"content": "Wait so when you clone from scratch, it works Ok?",
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"content": "can anyone indicate why this is happening:\n```\nRequested to load FluxClipModel_\nLoading 1 new model\nclip missing: ['text_projection.weight']\nE:\\comfyui2\\ComfyUI\\comfy\\ldm\\modules\\attention.py:407: UserWarning: 1Torch was not compiled with flash attention. (Triggered internally at ..\\aten\\src\\ATen\\native\\transformers\\cuda\\sdp_utils.cpp:455.)\n out = torch.nn.functional.scaled_dot_product_attention(q, k, v, attn_mask=mask, dropout_p=0.0, is_causal=False)\n```",
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"content": "But only the sub module portion",
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"timestamp": "2024-08-15T15:24:05.278+02:00",
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"content": "Is failing?",
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"timestamp": "2024-08-15T15:24:13.592+02:00",
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"content": "`clip missing: ['text_projection.weight']`",
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"content": "seems like it s all standard",
"author": {
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"content": "I have a weird issue, but on cloud it does not allow me to rename or copy the \"*.env\" file. It needs character before the \".\". On my local computer on windows it is of course with no problem.\nAnyone has encountered this problem?",
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"content": "you mean on runpod?",
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"content": "linux?",
"author": {
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"content": "i am using vast.ai , but yeah on linux through jupyterlab",
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"content": "correct",
"author": {
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"content": "You can include it on the run comand as well. so \n```\nHF_TOKEN=my_token python run.py path/to/config\n```",
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"content": "oh thanks!",
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"content": "it does not work. I get that error when trying to run the git submodule command",
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"content": "if you are on windows, it hates long path names and some of the submodules have long paths. So you need to store the toolkit in something short like `C:\\ai\\ai-toolkit` if you have it in `C:\\my super cool stuff\\other_long_folders` etc, the git submodule command will fail.",
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"content": "J:\\Flux training\\ai-toolkit>git submodule update --init --recursive\n 0 [main] sh 491 dofork: child -1 - forked process 21652 died unexpectedly, retry 0, exit code 0xC0000142, errno 11\nC:/Program Files/Git/mingw64/libexec/git-core\\git-submodule: fork: retry: Resource temporarily unavailable\n1075599 [main] sh 491 dofork: child -1 - forked process 16880 died unexpectedly, retry 0, exit code 0xC0000142, errno 11\nC:/Program Files/Git/mingw64/libexec/git-core\\git-submodule: fork: retry: Resource temporarily unavailable\n3138456 [main] sh 491 dofork: child -1 - forked process 4864 died unexpectedly, retry 0, exit code 0xC0000142, errno 11\nC:/Program Files/Git/mingw64/libexec/git-core\\git-submodule: fork: retry: Resource temporarily unavailable\n7204703 [main] sh 491 dofork: child -1 - forked process 1348 died unexpectedly, retry 0, exit code 0xC0000142, errno 11\nC:/Program Files/Git/mingw64/libexec/git-core\\git-submodule: fork: retry: Resource temporarily unavailable\n15270422 [main] sh 491 dofork: child -1 - forked process 10384 died unexpectedly, retry 0, exit code 0xC0000142, errno 11\nC:/Program Files/Git/mingw64/libexec/git-core\\git-submodule: fork: Resource temporarily unavailable",
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"content": "Oh, that path should work. hm..",
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"content": "very strange.Just tried on my work PC and it installed fine. but I don't want to do training on this machine.",
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"content": "How long has it been since you rebooted the machine with the git problem",
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"content": "You’re running it in mingw it looks like?",
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"content": "Try with Powershell!",
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"content": "Or vanilla terminal?",
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"content": "let me try that now. brb probably a long time. ok. I'll reboot first.",
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"content": "seeing this message now on start of training on linux, its new",
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"content": "The module 'mediapipe' is not installed. The package will have limited functionality. Please install it using the command: pip install 'mediapipe'",
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"content": "@Ostris",
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"content": "any ideas? session is running ok it seems",
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"content": "same error after rebooting and using powershell",
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"content": "damn. wonder if I need to reinstall git.",
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"content": "i finally downloaded everything and started my first training!\n\nbut i'm getting around 10s/it on a 3090, with 21.5GB VRAM usage, on windows 10\n\nis that natural? or should it be faster than that?",
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"content": "It shoudl be faster, it is probably doing offloading. I think the windows driver does that automatically. It shoudl be around 3-5 sec/iter on a 3090 (i think)",
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"content": "is there a fix for this issue?",
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"content": "4.56s/it 3ANDY YA M3ALEM",
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"content": "windows or linux?",
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"content": "How many it/s in flux generation",
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"content": "i forgot, but it works fine in comfy\n\nbut with AI toolkit, the sample generation takes a lot of time, more than a minute for each image with 20 steps",
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"content": "A5000 24gb vram 5.5 ish on windows 11",
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"content": "A6000 on Runpod is 2.5 \uD83D\uDE00",
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"content": "yup, on 3090ti as main gpu (using it for monitors too) getting about 3.5-6 s/it",
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"content": "those numbers are nice \n10s/it is way too slow",
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"content": "going up to 6 and 7 if i am using photoshop and youtube video runing",
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"content": "probably a dependency missing for me? like an attention optimizer or something ..",
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"content": "what is your regular flux generation speed in comfy ?",
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"content": "if you can use your igpu for your monitor it will leave you more vram, how much system memory have you?",
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"content": "can i use two gpu in training through pci e x16 + x4 ?",
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"content": "there isnt multi gpu yet but hopefully coming soon",
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"content": "but you can use on kohya and swarm ui",
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"content": "allthough kohya isnt ready for flux yet",
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"content": "but swarm only for image generation",
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"content": "i guess it was 1.2s/it or something like that",
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"content": "but the training is taking les than 24GB \nit's taking 21.5GB so there is some room left",
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"content": "yes again thats normal, you want a bit of overhead and unfortunately there is a 36gb option",
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"content": "me 1.48s/it and for 25step it takes 38 second so you are good to go in generation and the issue in training only يابختك",
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"content": "what rank and alpha are doing? \nme \n32\n32",
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"content": "tried 32 with yesterday and now doing 64 same vram consumption",
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"content": "that's good to hear",
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"content": "no low vram option in config right ?",
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"content": "for me i didn't use the low vram option\nand i kept EMA training on (it says it will be slower but better quality)",
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"content": "EMA training where i can find that option",
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"content": "no need for lol vram, models load in memory FP16",
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"content": "if your training data is ready how much does it cost you to train achracter model online ?",
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"content": "a 3-4 hour rrun is about 8 dollars",
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"content": "I wonder what is your best setting for character training with small photo assets",
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"content": "the default config is very close to perfect except i change LR to 1e-4 io run for 4000 steps and most times see good characters at that",
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"content": "with that learning rate i see perfect result after (4250-6000)",
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"content": "20 img rank 32",
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"content": "on ai toolkit? yes i saw that until a code update yesterday now its much quicker",
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"content": "noice, will see",
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"content": "does anyone use any monitoring tools to see the loss function and other graphs for flux?",
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"content": "OSError: We couldn't connect to 'https://huggingface.co' to load this model, couldn't find it in the cached files and it looks like https://huggingface.co/univerlist/runpod-baris is not the path to a directory containing a config.json file.\nCheckout your internet connection or see how to run the library in offline mode at 'https://huggingface.co/docs/diffusers/installation#offline-mode'\n\ncant fix thiss",
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"content": "you should create a token in huggin face",
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"content": "i already did also put it in env file",
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"content": "did you edited the config file the model location path ?",
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"content": "nah it is empty",
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"content": "what should i put",
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"content": "any example could u share ?",
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"content": "nothing you should leave it at it is and the script will download all checkpoints",
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"content": "HF_TOKEN=your_key_here",
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"content": "could u check dm",
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"content": "Hello, I just trained a Lora for 2500 steps, sample images are fine, but when I put the Lora in Comfyui, it does practically nothing. Do I need to convert the Lora or something?",
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"content": "I trained it on windows, I had no problems so far while training",
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"content": "so you took all the safetensors and put them in the lora directory and then in your workflow you set your flow to FP16 and used load lora yes?",
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"content": "Like, but I think I might off figured it out. Reducing the denoise seems to help",
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"content": "flux needs 20 cfg for dev, loras dont play well with Schnell yet",
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"content": "I'm using fp8 though, maybe it's because of that?\nIn any case the lora worked but I have to set the strength over 1.8 for it to work",
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"content": "FP8 isnt great with loras made with FP16",
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"content": "plus 1.8 means your lora is underbaked",
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"content": "Using dev, Is this one?",
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"content": "Hi People, trying to train my first Lora.\nfollowed to whole instruction amd then setup the yaml with my local model , image and output path but for some reason it doesnt take my model path and dosent connect to Hf although i have my token as .env file?\n\ncan anybody help me pls?\nRunning job: AudiQ6 e-tron\n#############################################\n\n\nRunning 1 process\nLoading Flux model\nLoading transformer\nError running job: We couldn't connect to 'https://huggingface.co/' to load this model, couldn't find it in the cached files and it looks like C:/tools/StabilityMatrix/Packages/ComfyUI/models/unet/flux\\transformer is not the path to a directory containing a config.json file.\nCheckout your internet connection or see how to run the library in offline mode at 'https://huggingface.co/docs/diffusers/installation#offline-mode'.\n\n========================================\nResult:\n \n0 completed jobs\n1 failure\n========================================\nTraceback (most recent call last):\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\venv\\lib\\site-packages\\diffusers\\configuration_utils.py\", line 379, in load_config\n config_file = hf_hub_download(\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\venv\\lib\\site-packages\\huggingface_hub\\utils_deprecation.py\", line 101, in inner_f\n return f(*args, **kwargs)\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\venv\\lib\\site-packages\\huggingface_hub\\utils_validators.py\", line 106, in _inner_fn\n validate_repo_id(arg_value)\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\venv\\lib\\site-packages\\huggingface_hub\\utils_validators.py\", line 154, in validate_repo_id\n raise HFValidationError(\nhuggingface_hub.errors.HFValidationError: Repo id must be in the form 'repo_name' or 'namespace/repo_name': 'C:/tools/StabilityMatrix/Packages/ComfyUI/models/unet/flux\\transformer'. Use repo_type argument if needed.\nDuring handling of the above exception, another exception occurred:",
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"content": "Traceback (most recent call last):\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\run.py\", line 90, in <module>\n main()\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\run.py\", line 86, in main\n raise e\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\run.py\", line 78, in main\n job.run()\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\jobs\\ExtensionJob.py\", line 22, in run\n process.run()\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\jobs\\process\\BaseSDTrainProcess.py\", line 1230, in run\n self.sd.load_model()\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\toolkit\\stable_diffusion_model.py\", line 484, in load_model\n transformer = FluxTransformer2DModel.from_pretrained(\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\venv\\lib\\site-packages\\huggingface_hub\\utils_validators.py\", line 114, in _inner_fn\n return fn(args, **kwargs)\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\venv\\lib\\site-packages\\diffusers\\models\\modeling_utils.py\", line 612, in from_pretrained\n config, unused_kwargs, commit_hash = cls.load_config(\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\venv\\lib\\site-packages\\huggingface_hub\\utils_validators.py\", line 114, in _inner_fn\n return fn(args, **kwargs)\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\venv\\lib\\site-packages\\diffusers\\configuration_utils.py\", line 415, in load_config\n raise EnvironmentError(\nOSError: We couldn't connect to 'https://huggingface.co/' to load this model, couldn't find it in the cached files and it looks like C:/tools/StabilityMatrix/Packages/ComfyUI/models/unet/flux\\transformer is not the path to a directory containing a config.json file.\nCheckout your internet connection or see how to run the library in offline mode at 'https://huggingface.co/docs/diffusers/installation#offline-mode'.",
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"content": ".env ---- HF_TOKEN=your_key_here",
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"content": "i did that",
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"content": "did you check all the boxes when you set it up?",
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"content": "still giving me the same error",
"author": {
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"content": "on huggingface",
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"content": "all the read boxes",
"author": {
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"content": "yes all the read write boxes",
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"content": "do I have to check all",
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"content": "I thought 2.5k steps would seem enough, at least on the sample photos it's great",
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"content": "are you sure you didnt save the .env file as .env.txt",
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"content": "are you on windows",
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"content": "I'm on windows, I had no problems training though",
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"content": "nope it says env file",
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"content": "so wierd",
"author": {
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"content": "in the error its asking for a config.json",
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"content": "are you in the venv did you activate it?",
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"content": "worked now",
"author": {
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"content": "Changed it to og path, now is downloading from HF, although I wanted to use it from my localdrive",
"author": {
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"content": "Is there a way to do that too?",
"author": {
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"content": "now I get this after chaching latents to disk\n\n - Found 35 images\nBucket sizes for C:/Users/RAIIN Studios/Documents/training/datasets/audiQ6:\n1024x1024: 35 files\n1 buckets made\nCaching latents for C:/Users/RAIIN Studios/Documents/training/datasets/audiQ6\n - Saving latents to disk\nCaching latents to disk: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████| 35/35 [00:03<00:00, 9.25it/s]\nGenerating baseline samples before training\nAudiQ6e-tron: 0%| | 0/3000 [00:00<?, ?it/s]Error running job: The size of tensor a (128) must match the size of tensor b (4) at non-singleton dimension 3\n\n========================================\nResult:\n - 0 completed jobs\n - 1 failure\n========================================\nTraceback (most recent call last):\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\run.py\", line 90, in <module>\n main()\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\run.py\", line 86, in main\n raise e\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\run.py\", line 78, in main\n job.run()\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\jobs\\ExtensionJob.py\", line 22, in run\n process.run()\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\jobs\\process\\BaseSDTrainProcess.py\", line 1701, in run\n loss_dict = self.hook_train_loop(batch)\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\extensions_built_in\\sd_trainer\\SDTrainer.py\", line 1493, in hook_train_loop\n loss = self.calculate_loss(\n File \"C:\\Users\\RAIIN Studios\\Documents\\training\\ai-toolkit\\extensions_built_in\\sd_trainer\\SDTrainer.py\", line 388, in calculate_loss\n loss = loss * timestep_weight\nRuntimeError: The size of tensor a (128) must match the size of tensor b (4) at non-singleton dimension 3\nAudiQ6e-tron: 0%|",
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"timestamp": "2024-08-15T18:07:28.777+02:00",
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"content": "what did you change in the config?",
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"content": "currently it seems it doestnt support batch size \n```\nraceback (most recent call last):\n File \"/notebooks/ai-toolkit/run.py\", line 90, in <module>\n main()\n File \"/notebooks/ai-toolkit/run.py\", line 86, in main\n raise e\n File \"/notebooks/ai-toolkit/run.py\", line 78, in main\n job.run()\n File \"/notebooks/ai-toolkit/jobs/ExtensionJob.py\", line 22, in run\n process.run()\n File \"/notebooks/ai-toolkit/jobs/process/BaseSDTrainProcess.py\", line 1701, in run\n loss_dict = self.hook_train_loop(batch)\n File \"/notebooks/ai-toolkit/extensions_built_in/sd_trainer/SDTrainer.py\", line 1493, in hook_train_loop\n loss = self.calculate_loss(\n File \"/notebooks/ai-toolkit/extensions_built_in/sd_trainer/SDTrainer.py\", line 388, in calculate_loss\n loss = loss * timestep_weight\nRuntimeError: The size of tensor a (64) must match the size of tensor b (4) at non-singleton dimension 3\n\n```",
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"timestamp": "2024-08-15T18:09:43.972+02:00",
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"content": "oh yeah, I need to talk a look at this today. Should be an easy fix.",
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"content": "in yaml?",
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"content": "Why NF4 have error why my training Lora Model. FP8 its worked good. How fix this?",
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"content": "now it works",
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"content": "thx a lot for helping me!",
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"content": "no problem we all help each other",
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"content": "you cant officially train on these and results will be very very mixed",
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"content": "NF4 is even less quality than FP8",
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"content": "damn i download all 3 models \uD83C\uDF6E",
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"content": "what u do you have? are you concern with speed or quality?",
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"content": "word!",
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"content": "finally got it working, getting 43.11 s/it on a 3090 non ti. that normal?",
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"content": "If I use my custom LoRA with chained with realism lora in my dev wf it needs 11.91s/it on 4090 24gb vram + 128gb ram, is that normal?",
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"content": "Comfy or forge? Forge have OOM with lora in random moments...",
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"content": "ok interesting, with one lora im back to 1.2 sec",
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"content": "Just reinstalled aitoolkit: Windows 11 Pro, 4090\n\non first run (2nd attempt, I completely deleted the first attempt), I get this issue: (enclosed in message.txt)",
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"content": "my last run this came up and didnt impact the run that i could see, but best to install before next one its python framework",
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"content": "can i somehow set when the generations will begin during the training and not on set invervals every 250 steps? For example the first 1000 steps it extend the training by useless generations which take long time.",
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"content": "Out of Memory. You have overflowed VRAM and it dumped some part of the model onto the CPU RAM, causing the speed to drop.",
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"content": "Yeah fixed it but unloading Chache and model and then running it again",
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"content": "For some reason it works faster 5,6s/it for 10 images now",
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"content": "I have similar issue after updating to the latest version. It's actually not a real issue because the script is still running.\nFunny enough, I had this in the exact same line on SDTrainer.py, but it's just a warning about deprecated method:\n```\nSDTrainer.py:61: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.\n self.scaler = torch.cuda.amp.GradScaler()\n```",
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"content": "ow, it's actually the exact same issue, I didn't scroll to the right lol",
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"content": "Got this one right after `Generating baseline samples before training`, but also didn't stopped the process:\n```\nai-toolkit\\venv\\Lib\\site-packages\\torch\\utils\\checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead.\n with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined]\n```",
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"content": "These warning can be ignored, unless thr program crashed when they happened",
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"content": "hi there",
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"content": "anyone has tried to run this on runpod",
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"content": "im getting error with the path for the dataset",
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"content": "nvm got itXD",
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"content": "`\\\\ fixes that`",
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"content": "yeh that was the thing, i went back and see the example file",
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"content": "hmm can i change the storage of the pod? cuz i think it run out of space",
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"content": "i run locally but maybe someone here can help",
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"content": "47.16s/it with a 3090 sound about right?",
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"content": "no that doesn't sound right \nyou are probably going over the 24GB of VRAM, idk, just a guess",
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"content": "4090 im getting 2.2s/it",
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"content": "Well its weird because it says that sometimes but right now it shows this. 2264/3000 [3:37:17<1:21:20, 6.63s/it, lr: 1.0e-04 loss: 8.718e-02]",
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"content": "@Ostris \ni noticed this error message in the console: (could it be the reason i'm getting 10s/it with my 3090?)\n\nA:\\ai-toolkit\\venv\\Lib\\site-packages\\transformers\\models\\clip\\modeling_clip.py:480: UserWarning: 1Torch was not compiled with flash attention. (Triggered internally at C:\\actions-runner\\_work\\pytorch\\pytorch\\builder\\windows\\pytorch\\aten\\src\\ATen\\native\\transformers\\cuda\\sdp_utils.cpp:555.)\n attn_output = torch.nn.functional.scaled_dot_product_attention(\nA:\\ai-toolkit\\venv\\Lib\\site-packages\\torch\\utils\\checkpoint.py:1399: FutureWarning: `torch.cpu.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cpu', args...)` instead.\n with device_autocast_ctx, torch.cpu.amp.autocast(**cpu_autocast_kwargs), recompute_context: # type: ignore[attr-defined]",
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"content": "you using 24gb config? what changes",
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"content": "sorry i didn't properly understand your question .. \n\nand yeah i'm using the flux 24gb config",
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"content": "linux?windows? what else is running",
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"content": "windows 10\nnothing else is running\nand my gpu is doing the display too, cuz i have a cpu without graphics (but i don't think that's the reason right?) \nalso the training takes 21.5 GB VRAM so there is plenty of room left",
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"content": "im not sure then",
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"content": "id update drivers, rule out anything that may be interfering",
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"content": "like what",
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"content": "whats your gpu usage, cpu usage and ram usage % wise when your not training and nothing is clearly open",
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"content": "any background tasks you may be overlooking?",
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"content": "hmm everything went fine till chan chan chaaaan",
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"content": "any ideas?",
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"content": "when i'm not training: \n* 0.1GB gpu, and idk if there are any other numbers for the gpu to check, i don't think it would doing much\n* 5 or 6 GB RAM from a total of 40GB \n* cpu usage is minimal, 20% at the max, usually around 5%\n\nwhen training: \n* 21.5 to 21.9 GB VRAM , 100% Cuda\n* 6 GB RAM\n* 5% to 20% cpu usage",
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"content": "i think you have to write the images folder directory correctly, like copy the whole file directory starting with the disk's letter \n\nalso if you are on windows, i guess you have to change \" \\ \" to \" \\ \\ \" in order for it to work",
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"content": "meaning you have to use two back slashes instead of one",
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"content": "Well if i were you my next thing I would do is reinstall ai-toolkit to a fresh install and makesure you didnt miss anything.\n\nAlso the GPU works normal speeds for everything else? any chance your thermal throttling from overheat?",
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"content": "this is runpod on linux, also my first time xD",
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"content": "if everything works ill make a tutorial, lots of stuff missing \uD83D\uDE1B",
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"content": "at first i was using afterburner to limit the GPU temp to 70, and it was giving me 18s/it\ni raised the temp limit and made it prioritise performance and i got 10s/it \n\nshould i try to let is loose completely and see if it improves ?",
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"content": "what you do with your GPU is up to you but it sounds like you found your answer",
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"content": "i'll try it right now",
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"content": "i dont use anything like afterburner for 1.5 years of off and on training on my 4090 no issues",
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"content": "i turned it off completely and it's still at 9.3s/it instead of 9.6s/it , so only a very small improvement",
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"content": "when this training finishes, i'll try updating the drivers, maybe that would help",
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"content": "hey a quick question: \nwhat's the highest learning rate you could set for Flux training? and what's the least amount of steps to accompany that for a successful training ..",
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"content": "It seems to start learning right away within a few hundred, okay-ish results 1000-1500. 2k/3k/4k constant improvements after 4k not much",
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"content": "at what learning rate?",
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"content": "i used the default 1e-4 and it didn't learn anything noticeable for 2000 steps \n\nbut i'm not using caption tho! only the images and the trigger word (written in the config)\n\n(i just wanted to do a quick test after installing anything so i didn't prepare captions for my images)",
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"content": "ive found trigger words to be a mixed bag in my experience so far",
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"content": "I would caption, also are you training a character/person/concept/style?",
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"content": "how far is what your training from the models current knowledge",
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"content": "i'm starting with a concept, which is not well represented in the model\n\nbut i'm interested in training everything from characters to people to concept to styles\n\nso any info you can share with me is appreciated",
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"content": "and i'll try captioning next time and see if that helps",
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"content": "for the trigger do I actively need to add [trigger] to the .txt files or will it be automatically added?",
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"content": "according to the config file, it sounds like you either have to write [trigger], or it has to be already written in the prompt",
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"content": "that's if you want all the samples to include the trigger word\nmaybe you want a sample without the trigger word",
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"content": "trigger doesnt seem to matter for some tasks at least",
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"content": "ive been training with it and it doesn't seem to matter on inference",
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"content": "so when my training finished the images in my output samples folder look amazingly like my goal person, but when I create images in comfy they do not. Wonder why that would be?",
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"content": "close comfy and do a git pull in the directory",
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"content": "see if that fixes it",
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"content": "I ran an update, I think I just may not know how to load loras properly in comfy. I am very new. I will try that though.",
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"content": "its model only lora loader",
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"content": "you stick it between the model loader and the sampler",
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"content": "Let me try that.",
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"content": "Hey quick question...training a LoRA on a single subject was easy enough, but I'd like to try training a style LoRA next. Do you just caption your images normally and not give the trainer a trigger keyword? This is all new to me.",
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"content": "this is my workflow. Does this look right? as far as where I have the lora placed?",
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"content": "For me, it works much better when the LoraLoader is between the model and the BasicGuider *and* between the model and the BasicScheduler",
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"content": "Is there a strength difference necessary to apply a lora accurately to fp8 vs fp16? I'm seeing more accurate results on fp8 with 1.5 but I'm not sure if that's due to the model or something else",
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"content": "I feel like I saw others have a similar experience but I never saw if varying the strength per model became, like, the accepted best practice or if there was some other reason for this inconsistency",
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"content": "same issue.. Have you resolved it?",
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"content": "I had to put my LoRA strength to 1.3 for it to work well",
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"content": "i set the strength 2.0, but I'm still not getting the same results as the training sample.",
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"content": "anyone running comfyui on mac apple m1 with flux",
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"content": "use `/` before workspace",
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"content": "Btw for all of u peeps that don’t want to caption ur self and seek for in depth captions. \nThis tool was def a game changer for me. There’s probably a comfy alternative but I like it especially because of the Tag manage part, where it creates a prompt matrix for u",
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"content": "this workflow uses florence",
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"content": "same problem here - great image samples when training, but zero visible Lora impact when generating images using ComfyUI.",
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"content": "what version of Flux are you using?",
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"content": "Resolved the other issues, but now I have this one:\n\nError running job: 'utf-8' codec can't decode byte 0xff in position 0: invalid start byte",
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"content": "Nevermind, discovered it was the caption files. I converted all of them utf-16 to utf-8",
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"content": "I had to train up to 3.5k steps at least, now with strenght of 1.25 or something I get results",
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"content": "No need to convert the lora",
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"content": "If you are using anything but Flux Dev for workflows in comfy you have to turn the strength up on the Lora. Also I don’t think anything but Flux Dev works well with Loras",
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"content": "it only happened a few times but it shouldnt",
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"content": "iam using joblib to process the images in parallel",
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"content": "Thxxx, how many tokens of captions do u get per txt file?",
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"content": "Yeah fluxdev wf with Lora is the best, for best Lora strength is at 0,8",
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"content": "Is there a max of images that u can train?",
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"content": "I am noticing that natural language works much better than booru for flux too",
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"content": "me too.. the lora where I used tags in wd14 style only are a mess..",
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"content": "I'm still experimenting with this and have had decent results from my first few attempts at training but one thing that doesn't seem to work at all is when I specify a trigger word in the config. When I generate using the lora I've created the trigger word I have in the config does nothing at all",
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"content": "have you updated comfy?",
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"content": "also you dont need a trigger word in comfy if using load lora",
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"content": "I have, and it does work fine without a trigger word",
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"content": "I'm using forge now instead of comfy but I'd tried it on both",
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"content": "I'm just perplexed why the trigger word doesn't work at all",
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"content": "interesting i though SD forge would need it",
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"content": "using the trigger made no difference in forge yet if I just prompt \"a woman\" instead of the trigger I'd specified it works OK",
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"content": "thats so weird",
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"content": "Hi All, if my training is finished can i restart it from that end point by adding more steps and a start point in the config?",
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"content": "I believe so, yes. I haven't tried this myself",
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"content": "but it should just carry on",
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"content": "@Ostris thoughts?",
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"content": "yes it will continue if you add more steps",
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"content": "batch training is not working so well? when I tried 2 batch on runpod with 48 gb vram it just got slower.",
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"content": "CAn someone help me with this please? running on runpod",
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"content": "was just about to say I think you need a / before the workspace \uD83E\uDD23",
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"content": "happend to me yesterday",
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"content": "Anyone using Flux on Forge? Specfically Loras. I am finding the \"patching lora\" bit very slow on my 4090, I have to use you offload option otherwise it OOMs",
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"content": "I am, which version of the model are you using?",
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"content": "I'm on a 4090 as well",
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"content": "using flux1-dev-fp8 I haven't had any issues",
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"content": "I quickly tried flux1-dev-bnb-nf4-v2 and that did give me an OOM",
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"content": "flux1-dev-bnb-nf4-v2.safetensors as per I video I watched. TBH it ok without the loras. But as soon as I used my own fine tune its becomes a issue",
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"content": "give flux1-dev-fp8 a go",
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"content": "I FINALLY got it working. So, now that I finished training my first model, what Flux+Lora ComfyUI workflow can I use to run it, lol",
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"content": "Helllo! why do i get distorted faces? please help. job: extension\nconfig:\n name: OPA_RANK64\n process:\n - type: sd_trainer\n training_folder: P:\\DREAMBOOTH\\FLUX\\Opa\\model\n device: cuda:0\n network:\n type: lora\n linear: 64\n linear_alpha: 64\n save:\n dtype: float16\n save_every: 200\n max_step_saves_to_keep: 40\n datasets:\n - folder_path: P:\\DREAMBOOTH\\FLUX\\Opa\\img\n caption_ext: txt\n caption_dropout_rate: 0.05\n shuffle_tokens: false\n cache_latents_to_disk: true\n resolution:\n - 512\n - 768\n - 1024\n train:\n batch_size: 1\n steps: 5000\n gradient_accumulation_steps: 1\n train_unet: true\n train_text_encoder: false\n content_or_style: balanced\n gradient_checkpointing: true\n noise_scheduler: flowmatch\n optimizer: adamw8bit\n lr: 0.0004\n ema_config:\n use_ema: true\n ema_decay: 0.99\n dtype: bf16\n model:\n name_or_path: S:\\ai-toolkit\\black-forest-labs\\FLUX.1-dev\n is_flux: true\n quantize: true\n sample:\n sampler: flowmatch\n sample_every: 250\n width: 1024\n height: 1024\n prompts:\n - 'photo of a 20-year-old woman, medium shot, holding a coffe cup with text:\n ''OPA'' , and city in the background'\n neg: ''\n seed: 42\n walk_seed: true\n guidance_scale: 3\n sample_steps: 25\nmeta:\n name: OPA_RANK64\n version: '1.0'",
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"content": "i'm running a 3090 and it's taking 48s/it! is this normal adding the lora in?",
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"content": "flux its slow as fuck, im on 4070 ti, takes about 40s",
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"content": "u can try fp4",
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"content": "any one you want",
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"content": "I think he needs a workflow",
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"content": "I'm good fellas, I'm using this one:\n\nhttps://openart.ai/workflows/ailab/flux-lora-simple/gErKNyjsnetZpEgaMTrV",
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"description": "Created by: AILab: Lora: Aesthetic (anime) LoRA for FLUX https://civitai.com/models/633553 Crystal Style (FLUX + SDXL) https://civitai.com/models/274793",
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"content": "cofyanonymous.github.io/ComfyUI_examples/flux/ please follow this guide. it is proven to work",
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"content": "any examples \uD83D\uDE09",
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"content": "Got the Workflow going after some more troubleshooting. Images (101) were generated with Midjourney, trained on fal.ai at 4000 steps with a Learning Rate or 0.004. Good lord that was a lot of effort. But now, we can use srefs and other styles as a base for our Loras.",
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"content": "good good \uD83D\uDE1B",
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"content": "anyone have a good solution for human captioning locally?",
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"content": "for windows that is \uD83D\uDE26",
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"content": "so what's the word on running training on less than 24gb these days?",
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"content": "I hope they get it, but I think its gonna be higher and higher in the future",
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"content": "better save up for that upgrade",
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"content": "waiting for 5090 xD",
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"content": "5090 titan 48 vram",
"author": {
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"content": "Whats funny is that I got memory allocation errors, so some of the images didnt show in the review, but still generated in the outputs folder",
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"content": "bye bye beach, i got my 5090 and small pool at home XD",
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"content": "captioning workflow",
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"content": "anywho, going to upgrade from 16 gigs of RAM (system , not VRAM) and max it out at 96",
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"content": "Quick question that may have been asked but idk how or where yet:\n\n```\n Sign into HF and accept the model access here black-forest-labs/FLUX.1-dev\n Make a file named .env in the root on this folder\n Get a READ key from huggingface and add it to the .env file like so HF_TOKEN=your_key_here\n```\n\nThis section in the instructions, file named... just ```.env``` or does it need a file name as well as just an extension? Also, root on this folder... ? Which folder?",
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"content": "48gb is fine on the A6000 however training maxes out utilisation at 4gb",
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"content": "no just .env in the AI Toolkit root folder on windows not the same on linux",
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"content": "runpod?",
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"content": "HF_TOKEN=YOURKEY python run.py config/LORA_NAME.yaml",
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"content": "like this HF_TOKEN=hf_qlSDXpURszwaPhzOQQHsq python run.py config/filename.yaml",
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"content": "there u go \uD83D\uDE04",
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"content": "thats not my token before anyone asks \uD83D\uDE42",
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"content": "using that key right now \uD83D\uDE1B",
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"content": "dont forget its yaml not yml, @Ostris we need to tidy up and correct the github instructions, can i do it please?",
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"content": "Thanks again. I hate linux. \uD83D\uDE2E‍\uD83D\uDCA8",
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"content": "its a custom one, ai training ai",
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"content": "The first one I made locally is aweful which if fine because I just needed the damn thing to run, so everything is on default, but the next one....",
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"content": "flux give her a boob job, but at least i dont need to go for reactor now",
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"content": "lol, its all good though",
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"content": "is there supposed to be a mediapipe error?",
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"content": "yeh i was editing right now XD",
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"content": "Like as in it's not there?",
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"content": "i see the mediapipe error and the abu thing error sometimes too, means there are updates",
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"content": "@Weatherby I installed it anyways just to get rid of it",
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"content": "I dont know if its needed or not",
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"content": "Ok, I was going to do that but it started training anyway.",
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"content": "# Tutorial: Using a Text-to-Image Generation Pipeline\n\nThis tutorial demonstrates how to set up and use a text-to-image generation pipeline with a pre-trained model and LoRA weights.\n\n1. Import required libraries:\n ```python\n from diffusers import ImageGenerationPipeline\n import torch\n ```\n\n2. Load the pre-trained model:\n ```python\n pipe = ImageGenerationPipeline.from_pretrained(\"organization/model-name\", torch_dtype=torch.bfloat16)\n ```\n\n3. Load LoRA weights (if applicable):\n ```python\n pipe.load_lora_weights(\"path/to/lora_weights.safetensors\")\n ```\n\n4. Move the pipeline to GPU for faster inference:\n ```python\n pipe = pipe.to(\"cuda\")\n ```\n\n5. Generate an image:\n ```python\n prompt = \"a 3d image in custom style of a man feeding his dog\"\n img = pipe(prompt).images[0]\n ```\n\n6. Save the generated image:\n ```python\n img.save(\"output.png\")\n ```\n\nNote: The actual model names and paths used in this tutorial are \"black-forest-labs/FLUX.1-dev\" for the pre-trained model and \"cartwheel_facesv1.safetensors\" for the LoRA weights. Replace these with appropriate values for your use case.\n\nRemember to handle potential errors and exceptions in a production environment. The tutorial assumes you have the necessary libraries installed and a CUDA-compatible GPU available.",
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"content": "OK, in the config it asks for image directory. (damn linux again) what should that be to put it in ```workspace/img```?",
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"content": "I tried ```img``` says it can't find it.",
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"content": "you need to create it",
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"content": "Oh, it's there. I just mean what is the directory path it's expecting to locate it",
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"content": "workspace/ai-toolkit/images or whatever you call ii",
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"content": "it",
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"content": "I think I got it to find it but then got this",
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"content": "OSError image file is truncated",
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"content": "you did upload your images right?",
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"content": "add / to /workspace/img",
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"content": "Yes. \n(And I did add the / and it did find them)",
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"content": "Might have been a corrupted upload",
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"content": "hello everyone i need some help. i have trained a lora model, in output of trainer i've got results, but in comfyui flux just ignores my Lora. why? \n\noutput of training is ok",
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"content": "One image was cropped as if half uploaded, and I just reuploaded and it's no longer like that. Size is different too.",
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"content": "yikes",
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"content": "ok great rerun",
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"content": "Yep, that was it.\n\nThank you all for the help. \uD83D\uDE42",
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"content": "have fun \uD83D\uDE04",
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"content": "will run a new one tonight with captions",
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"content": "https://tenor.com/view/bh187-mr-bean-thumbs-up-i-got-this-you-got-it-gif-19287034",
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"content": "I ran my set through supir and let llava caption it.. *fingers crossed*",
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"content": "captions are the bane of my life",
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"content": "Yeah, I have a love hate relationship with them as well.",
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"content": "# I decided to create a FAQ using msgs from the server and Gemini\n# AI Toolkit for Flux LoRA Training - FAQ\nThis FAQ addresses the most common and pressing questions regarding AI Toolkit for Flux LoRA training, including explanations of key config settings\n## General\n**Q: What is AI Toolkit?** \nA: AI Toolkit is a collection of scripts for training and manipulating AI models, with a focus on Stable Diffusion and Flux. It currently features a powerful and popular script for training Flux LoRAs.\n\n**Q: What are LoRAs?** \nA: LoRAs (Low-Rank Adaptations) are small files that contain learned weight differences applied to a base model. They offer a lightweight and efficient way to customize a model for specific styles, concepts, or subjects.\n\n**Q: Which Flux model can I train with AI Toolkit?** \nA: Currently, AI Toolkit only supports training LoRAs for\u00A0**Flux Dev**.\n\n**Q: Can I train a LoRA on a 4090 or other consumer GPUs?** \nA: Yes, the script is optimized to run on 24GB GPUs and has been successfully used on 4090s, 3090s, and A5000s.\n\n**Q: What is the difference between AI Toolkit and other LoRA trainers like SimpleTuner or Kohya_ss?** \nA: AI Toolkit stands out for its ease of use, specific focus on Flux, and unique features. It employs a YAML config file for easy parameter adjustment, making it beginner-friendly. It also includes innovative options like\u00A0linear_timesteps\u00A0for improved training. While other trainers might offer more features or support for different models, AI Toolkit excels in its simplicity and effectiveness for Flux LoRA training.\n\n**Q: Can I use the LoRAs trained with AI Toolkit in other applications or with different Flux versions?** \nA: AI Toolkit currently trains LoRAs specifically for Flux Dev. While they might work with Flux Schnell, results may be inconsistent. They won't work with other models like Stable Diffusion. Compatibility with other applications depends on their support for Flux Dev LoRAs.",
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"content": "## Installation and Setup\n### Dataset Preparation\n**Q: How many images do I need for training?** \nA: It depends on what you are training:\n- **Characters/Subjects:**\u00A010-50 high-quality images usually suffice.\n- **Styles:**\u00A040-150 images work well. Over 200 can lead to inconsistent results.\n- **Very Large Datasets (50k+):**\u00A0Excessive for LoRAs and can cause performance issues.\n\n**Q: How should I caption my images?** \nA:\n- **Use Natural Language:**\u00A0Write detailed descriptions of the content in each image, focusing on the subject and its features. Avoid mentioning the style itself.\n- **Consider Skipping:**\u00A0For characters, training without captions can be successful.\n- **Experiment with Tools:**\u00A0LLaVA, CogVLM, Florence 2, and Gemini Pro are good options. The\u00A0joy-caption-pre-alpha\u00A0space on Hugging Face is also recommended.\n\n**Q: Do I need to use regularization images?** \nA: Their effectiveness for Flux is still debated. They might benefit photorealistic subject training but are not necessary for characters. AI Toolkit lets you add a regularization dataset with\u00A0is_reg: true. Experiment with different\u00A0reg_weight\u00A0values to control their influence.\n\n**Q: What are the recommended image resolutions and aspect ratios for training?**\nA:\n- **Resolution:**\u00A0Start with 1024x1024. Flux handles different resolutions well, but 1024 is a good balance between detail and VRAM usage. You can experiment with other resolutions as needed.\n- **Aspect Ratios:**\u00A0You don't have to worry too much about aspect ratios. Flux's Rotary Positional Encoder allows it to learn from images with various aspect ratios effectively.",
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"content": "## Training\n### Beginner-Friendly Explanation of LoRA Parameters:\n- **Rank (linear):** Imagine LoRA as \"notes\" modifying the base model's \"song.\" Rank controls the number of these notes. Higher rank means more notes, potentially creating a more detailed LoRA but requiring more VRAM and risking overfitting. Lower rank means fewer notes, making it lightweight and versatile but possibly less detailed.\n- **Alpha (linear_alpha):**\u00A0This controls the \"volume\" of the LoRA's \"notes.\" A higher alpha increases the LoRA's influence on the base model, while a lower alpha makes its effect more subtle.\n- **Batch Size:**\u00A0How many images the model processes at once during training. A higher batch size can speed up training, but AI Toolkit currently limits it to 1 due to VRAM constraints. You can use Gradient Accumulation Steps (gradient_accumulation_steps) to simulate a higher batch size.\n- **Learning Rate:**\u00A0How quickly the LoRA learns from the training data. A higher learning rate leads to faster changes, but it can also make the training unstable or overfit easily. A lower learning rate is more cautious and stable but might require more steps to converge.\n- **Steps:**\u00A0The total number of iterations the model goes through during training. More steps mean more learning, but also take more time and might lead to overfitting if the learning rate is too high.\n- **Gradient Accumulation Steps:**\u00A0A way to simulate a higher batch size on limited VRAM. Instead of processing a large batch at once, it accumulates the gradients from smaller batches and updates the LoRA less frequently.\n- **EMA (Exponential Moving Average):**\u00A0A technique that smooths out the LoRA's weights during training, improving stability and often leading to better final results.\n- **Data Type (dtype):**\u00A0The precision of the numbers used during training.\u00A0bf16\u00A0is a good balance between speed and accuracy for Flux LoRA training.",
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"content": "### Key Config Settings Explanation:\n- **quantize:**\u00A0Enables 8-bit mixed precision training. Leave it as\u00A0true\u00A0for most cases.\n- **datasets:**\u00A0Defines your training dataset(s). You can add multiple datasets here.\n - **folder_path:**\u00A0Path to your image folder.\n - **caption_ext:**\u00A0File extension for your caption files (e.g.,\u00A0txt).\n - **caption_dropout_rate:**\u00A0Probability of dropping out a caption token during training. Can help prevent overfitting.\n - **resolution:**\u00A0Resolutions to train on. Experiment with different values, but 1024 is a good starting point.\n - **is_reg:**\u00A0Set to\u00A0true\u00A0for regularization datasets.\n - **num_repeats:**\u00A0Controls how many times a dataset is repeated during training. Useful for balancing datasets of different sizes.\n- **train:**\u00A0Contains parameters for the training process.\n - **steps:**\u00A0Total number of training steps.\n - **gradient_accumulation_steps:**\u00A0Simulates a higher batch size by accumulating gradients.\n - **train_unet:**\u00A0Train the UNet model. Keep this as\u00A0true.\n - **train_text_encoder:**\u00A0Keep this as\u00A0false. Training the text encoder is not supported yet.\n - **content_or_style:**\u00A0Leave it at\u00A0balanced\u00A0for now.\n - **gradient_checkpointing:**\u00A0A memory saving technique. Can be enabled if you have limited VRAM.\n - **optimizer:**\u00A0adamw8bit\u00A0is the default and works well.\n - **lr:**\u00A0Learning rate. Start with 1e-4 or lower (you can read about learning rates below).\n - **ema_config:**\u00A0Configures EMA (Exponential Moving Average). Enable it with\u00A0use_ema: true.\n - **dtype:**\u00A0Data type for model calculations. Keep it as\u00A0bf16.\n - **linear_timesteps:**\u00A0Set to\u00A0true\u00A0to use the new experimental linear timestep weighting.\n - **reg_weight:**\u00A0Controls the influence of regularization datasets. Set a value between 0 and 1.\n- **model:**\u00A0Specifies details about the base Flux model.\n - **quantize:**\u00A0Enable 8-bit quantization. Leave it as\u00A0true.",
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"content": "### About learning rates\n**Lower Learning Rates:**\n- **8e-5:**\u00A0Many users find this to be a sweet spot, especially for character and style LoRAs. Offers a good balance between speed and stability.\n- **5e-5:**\u00A0A good choice for larger datasets (100+ images) where overfitting is a concern. Slower but can yield more nuanced results.\n- **4e-5:**\u00A0A safe bet for very large datasets (300+ images) to avoid aggressive learning and potential instability.\n\n**Higher Learning Rates:**\n- **2e-4:**\u00A0Potentially faster convergence, especially for smaller datasets and well-captioned images. However, increases the risk of overfitting or instability.\n- **3e-4:**\u00A0A more aggressive option that can work well for smaller datasets with strong stylistic consistency. Requires close monitoring for overfitting.\n- **4e-4:**\u00A0The previous default. Can still be effective for certain datasets, but generally, lower LRs are favored for Flux.\n\n**Choosing the Right Learning Rate:**\n- **Smaller datasets:**\u00A0Can often handle higher learning rates.\n- **Larger datasets:**\u00A0Need lower learning rates to avoid overfitting.\n- **Highly consistent images:**\u00A0Can tolerate higher learning rates.\n- **Diverse images:**\u00A0Might require lower learning rates for stability.\n- **Always monitor your training:**\u00A0Watch the sample images and the reported loss values to see if you need to adjust the learning rate.",
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"content": "### Common training questions\n**Q: Can I train multiple concepts or characters in a single LoRA?**\nA: Yes! You can train a single LoRA on multiple concepts, characters, or styles. Here's how:\n1. **Multiple Datasets:**\u00A0In your\u00A0config.yml\u00A0file, define multiple datasets under the\u00A0datasets\u00A0section. Each dataset can have its own\u00A0folder_path\u00A0and captions.\n2. **Balancing Influence:**\n - **num_repeats:**\u00A0Use this parameter to control how many times a dataset is repeated during training. If one dataset is smaller, you can set a higher\u00A0num_repeats\u00A0for it to balance its influence.\n - **reg_weight:**\u00A0If you are using a regularization dataset (is_reg: true), use\u00A0reg_weight\u00A0to control its impact on the training. A lower value gives it less influence.\n3. **Captioning:**\n - If you want the LoRA to learn specific keywords associated with each concept, make sure those keywords are present in the corresponding captions.\n - You can also use the\u00A0keep_tokens\u00A0parameter to ensure certain keywords never get dropped out during training.\n\n**Q: How do I use the generated latent cache?**\nA: The script automatically generates and uses a latent cache to speed up training. You don't need to manually interact with it. If you encounter issues or want to regenerate the cache, you can delete the `_latent_cache` folder within your dataset directory.\n\n**Q: What is the best learning rate to use?** \nA: Start with 1e-4 or lower. Experiment with different values depending on your dataset and observed overfitting.\n\n**Q: How many steps should I train for?** \nA: Start with 1000-2000 and monitor progress. Convergence can happen early, but quality often improves after initial regressions.\n\n**Q: The script doesn't support higher batch sizes. What can I do?** \nA: Use Gradient Accumulation Steps (gradient_accumulation_steps) to simulate a higher batch size.",
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"content": "**Q: What is\u00A0`linear_timesteps`?** \nA: This experimental feature attempts to improve composition and detail by using a different way of sampling training data. You can try setting it to\u00A0`true`, but it's still being tested.\n\n**Q: Can I resume training after stopping?** \nA: Yes, simply increase the step count in the config file and run the script again.\n\n**Q: Why are my sample images blurry?** \nA: Flux Dev can generate blurry images occasionally. Try these:\n- Change the seed\n- Decrease the guidance scale in the config file\n- Ensure ComfyUI is updated if using it for inference.\n\n**Q: I'm experiencing a slowdown during training. What can I do?** \nA: Potential causes and solutions:\n- **Windows Native:**\u00A0Potential memory leak issue. Consider using WSL.\n- **Large Datasets:**\u00A0Reduce the image count.\n- **High Resolution Buckets:**\u00A0Avoid resolutions larger than 1024.\n\n**Q: What is the\u00A0optimizer.pt\u00A0file for?** \nA: This file stores the optimizer state and is used for resuming training. It's not needed for inference.\n## Inference\n**Q: How do I use my trained LoRA for inference?** \nA: Use ComfyUI, ensuring it's updated for compatibility. Load the final\u00A0.safetensors\u00A0file using the Lora Loader node.\n\n**Q: My LoRA doesn't seem to be working in ComfyUI. What should I do?** \nA:\n- **Update ComfyUI:**\u00A0This often fixes compatibility issues.\n- **Increase LoRA Strength:**\u00A0Higher strength might be necessary, especially for bf16 LoRAs.\n- **Check for Errors:**\u00A0Look for errors in ComfyUI's console regarding lora loading.\n- **Fresh Install:**\u00A0A fresh install can resolve plugin conflicts.\n\n**Q: Why does inference with my LoRA take so long in ComfyUI?** \nA:\n- **VRAM Usage:**\u00A0Flux Dev and LoRAs are resource intensive. Ensure you have enough VRAM.\n- **Consider Offloading:**\u00A0Use the\u00A0--disable-smart-memory\u00A0flag in your ComfyUI start batch file or try offloading parts of the workflow to another GPU if you have multiple.",
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"content": "**Q: The generated images are not as good as the training samples. Why?** \nA:\n- **Update ComfyUI:**\u00A0This is crucial for compatibility.\n- **Experiment with LoRA Strength:**\u00A0Higher values might be needed, especially for bf16 LoRAs.\n- **Captioning:**\u00A0Ensure your prompts in ComfyUI align with the captions used during training.\n## Future Development\n**Q: Will there be multi-GPU support?** \nA: Yes, it's a high priority for future development.\n\n**Q: Are Slider LoRAs coming?** \nA: Yes, they are currently in development.\n\n**Q: Will there be a GUI?** \nA: A GUI and improved documentation are planned for the future.\n## Troubleshoot\n**Q: fbgemm.dll error**\nA:This is a torch bug on windows. There are some solutions here, but looks like the next release of torch will have it fixed https://discuss.pytorch.org/t/failed-to-import-pytorch-fbgemm-dll-or-one-of-its-dependencies-is-missing/201969/59\n\n**Q: I'm getting the \"No module named `dotenv`\" error. How do I fix it?**\nA: This usually means you are not running the script within the activated venv. Ensure you activated it using `python -m venv venv` or `python3 -m venv venv`\n\n### Disclaimer\nThis FAQ was compiled using an AI and, while it draws on community discussions and publicly available information, it may contain inaccuracies or outdated information. Always refer to official documentation and resources for the most up-to-date and accurate guidance.",
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"content": "I've been studying the topic of Flux LoRA training for the 2nd day and realized that there is a lot of information, so I decided to make a bit more beginner friendly",
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"content": "Um… is it? I didn’t mean to do that , though it works well.",
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"content": "Going to test it now.",
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"content": "what does it do",
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"content": "@Ostris seeing mediapipe and albumentation not installed warnings on linux and windows, anything i should do? apart from install them next time?",
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"content": "The mediapipe stuff is not used by the flux trainer so you probably don't need it",
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"content": "cheers",
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"content": "https://discord.com/channels/1144033039786188891/1272958459012448378/1272962321534156853 It should not be a huge difference on results, but is more balanced.",
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"content": "super. duper",
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"content": "Followed this guide https://www.youtube.com/watch?v=HzGW_Kyermg&t=3s But when I start training I get this error code",
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"content": "can you share your config",
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"content": "the intend on line with \"process\" was wrong",
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"content": "in yaml syntax it's important",
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"content": "try this one",
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"content": "And I also changed to double backslash in dataset path",
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"content": "because otherwise it recognised as escape character",
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"content": "@Ostris \n\nQ: I'm experiencing a slowdown during training. What can I do?\nA: Potential causes and solutions:\nWindows Native: Potential memory leak issue. Consider using WSL.\n\nis this the reason i'm having 9 to 10s/it in my 3090? (windows 10)\n\nand will there be a fix for it?",
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"content": "Models are being downloaded/Training is starting. Thanks \uD83D\uDC4D",
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"content": "Great!",
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"content": "Windows will do something to keep you from OOMing. IT is really cool for gaming, but kind of sucks for training. It will offload parts of the work off the gpu. It can do this aggresivly at times. On a 3090, if you are getting more than 5s/iter, this is likely what is happening.",
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"content": "how can i stop it \uD83E\uDD7A",
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"content": "WSL2 doesn't seem to slow down my 4090",
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"content": "what is WSL and how can i use it? if that fixes my issue i'll use it instead (and please tell me i won't have to download the models all over again \uD83E\uDD7A)",
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"content": "WSL is windows subsystem linux, its rather technical if you haven't heard of it before even",
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"content": "you install a linux distro inside your windows OS",
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"content": "wsl2 is an option that should work. However, if you are using your gpu for a monitor, you may be pushing the memory limit. Some people manage to get by, others don't. WSL does seem more efficient though.",
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"content": "what's weird is the training takes only 21.5 GB vtam \nso there is room left!",
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"content": "Most of my experience is directly on linux. I dont use windows much",
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"content": "for personal reference here. I run my 4090 on a WSL through remote desktop (Windows RDP). not sure what happens to the resources when im not actively viewing it. its not connected to a monitor at all",
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"content": "I get about 2.2s/it",
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"content": "is there a good tutorial or guide for WSL?",
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"content": "there should be official microsoft documentation online as well",
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"content": "Ubuntu is a good distro to start with. Note you can install a headless version of linux as your going to be running everything in CLI",
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"content": "thanks for you help guys! i really appreciate it",
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"content": "same gpu here, running on windows with 1.65s/it",
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"content": "4090, yes",
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"content": "post your config? (also im 4090) the other guy was 3090",
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"content": "i could easily switch to running on windows ofc",
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"content": "i assume configs can affect the training speed quite a bit",
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"content": "which config you mean?",
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"content": "your .yaml file your running",
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"content": "a few tweaks from default config",
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"content": "ill have to try native on windows then after this run",
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"content": "important to note that this is my 2nd PC so I have no monitor connected (RDP only) and the only thing running is the trainer",
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"content": "same boat here. (rdp only)",
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"content": "I run a 4070 on my primary pc, which until this past week was good enough for inference",
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"content": "that escalated quickly \uD83D\uDE06",
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"content": "Does anyone know where these models are downloaded? I assumed it would be in the ai toolkit folder. I installed on a separate drive because my C: doesnt have enough space. The download stalled because I noticed it was downloading these models on my C: drive. Where can I find the downloaded models so I can hopefully move them to secondary drive?",
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"content": "I'm on windows 11",
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"content": "the top one \uD83D\uDE42",
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"content": "<https://windirstat.net/>\n\nThis is how I find things to clear",
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"content": "make sure you know what your deleting ofc",
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"content": "you need to go into nvidia control panel and change cuda sysmem fallback to prefer no sysmem fallback",
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"content": "Don’t forget to set max performance while you are in there",
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"content": "downloading that DLL worked for me. for anyone else having this issue and doesnt know, but you have to put this DLL in your system32 folder",
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"content": "hi, does the .env go in the root of the a-toolkit folder? That's the part that wasn't clear.",
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"content": "Or does it go in the config?",
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"content": "ai-toolkit folder, near the run.py file",
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"content": "Hm. Ok, that's where t is.",
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"content": "```\nTraceback (most recent call last):\n File \"E:\\ai-train\\ai-toolkit\\run.py\", line 5, in <module>\n from dotenv import load_dotenv\nModuleNotFoundError: No module named 'dotenv'\n```",
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"content": "Getting this despite it being there",
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"content": "I'm on Windows. Running on powershell. It's not a .env.txt, it's just .env",
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"content": "Aha! One step further along nw.",
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"content": "`python -m venv venv` or `python3 -m venv venv`",
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"content": "yeah I ran that command. Getting a fbgemm.dll error now",
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"content": "which a quick gogle says I ineed to install VC_redist",
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"content": "so onward to that. Thank you!",
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"content": "hey scroll up to my comment a few lines up i just commented about this problem and that fix worked for me. just put the DLL in system32",
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"content": "hopefully it works for you too",
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"content": "hasn't stopped so far after that so so far so good. Fingers crossed. Until the next error at least. :D",
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"content": "```\nImportError: cannot import name 'packaging' from 'pkg_resources' (E:\\ai-train\\ai-toolkit\\venv\\Lib\\site-packages\\pkg_resources\\__init__.py)\n```",
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"description": "\uD83D\uDC1B Describe the bug Problem seems to arise when loading a model using install_py_dep_per_model=true which will upgrade the setuptools version to latest 70.0 and thus breaking the handler loading. So...",
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"content": "says to downgrade setuptools so I did that. Let's see.",
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"content": "holy shoot it's training!",
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"content": "unfortunately that didn't work either",
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"content": "```\nOSError: [Errno 22] Invalid argument: 'E:\\trainpics'\n```",
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"content": "that's where my training pictures are",
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"content": "It's copy/pasted directly from the file explorer URL bar",
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"content": "maybe it needs another backslash at the end?",
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"content": "which option is that?",
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"content": "Try to add another to the end, or to use double backslash",
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"content": "yea each \\ you have to add an extra \\",
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"content": "Stuck since the model update \uD83D\uDE26",
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"content": "Works so far. Thanks guys!",
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"content": "Morning all. Anyone need help?",
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"content": "Having the same issue, gets to 99% and just stops. Any fix?",
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"content": "do you have space on your runpod or is this local?",
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"content": "hmmmmm odd indeed",
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"content": "what flux model version are you using?",
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"content": "Hey, every time I start training, it takes 15 minutes to download the PyTorch model. Is there a way to download it locally so I don't have to fetch these files remotely?",
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"content": "tell me if you find a fix I've tried many things but nothing yet",
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"content": "you put it in your lora folder in comfy and use lora loader in workflow",
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"content": "I'm on windows 11",
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"content": "could it be something to do with image resolution? what resolution images are you using?",
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"content": "I'm getting 4.2s/it with a 4090 on native windows 11, 25 images with 1024x1024",
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"content": "thats about normal speed",
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"content": "fopr 24gb card",
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"content": "I saw some people getting 2.2s/it and 1.65s/it above, so I was wondering if Im missing something",
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"content": "whats your card again>? using default training settings?",
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"content": "pretty much default settings, with different LR",
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"content": "have anyone tried the xlabs controlnet?",
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"content": "I tried 2e-04, 3e-04",
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"content": "but it stays around 4.1s/it - 4.25s/it",
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"content": "thats normal like i said",
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"content": "u guys get images in 4 secs, amazing",
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"content": "oh ic XD",
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"content": "cuz i get like 40secs",
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"content": "end to end image on comfy with a lora and Flux dev is 25 seconds",
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"content": "oh wow, i actually got fbgemm.dll fixed, by throwing this file into system32 https://www.dllme.com/dll/files/libomp140_x86_64/00637fe34a6043031c9ae4c6cf0a891d/download",
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"content": "installing vc_redist and visual studio wasnt helping me",
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"content": "windows \uD83D\uDE04",
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"content": "how do u patch a lora?",
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"content": "Is model already patched? False\nWe are patching diffusion model, be patient please <-- this is with xlabs",
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