ScriptedAlchemy

{
     "tools": [
      {
        "type": "function",
        "function": {
          "name": "codebase_search",
          "description": "Find snippets of code from the codebase most relevant to the search query.\nThis is a semantic search tool, so the query should ask for something semantically matching what is needed.\nIf it makes sense to only search in particular directories, please specify them in the target_directories field.\nUnless there is a clear reason to use your own search query, please just reuse the user's exact query with their wording.\nTheir exact wording/phrasing can often be helpful for the semantic search query. Keeping the same exact question format can also be helpful.",
          "parameters": {
            "type": "object",
            "properties": {

mshumer

# Swift Language Fundamentals

Swift is a modern programming language for Apple platforms (iOS, macOS, etc.) with these key characteristics:

1. Core Features:
- Type inference for automatic type detection
- Optionals for safe handling of missing values
- Closures for flexible function passing
- Memory safety by design
- Built-in error handling

sayakpaul

from diffusers import FluxPipeline, AutoencoderKL
from diffusers.image_processor import VaeImageProcessor
from transformers import T5EncoderModel, T5TokenizerFast, CLIPTokenizer, CLIPTextModel
import torch
import gc


def flush():
    gc.collect()
    torch.cuda.empty_cache()

HongSiu

{
    "extra": {},
    "links": [
        [
            7,
            3,
            0,
            8,
            0,
            "LATENT"

laksjdjf

'''
https://arxiv.org/abs/2312.00858
1. put this file in ComfyUI/custom_nodes
2. load node from <loaders>

start_step, end_step: apply this method when the timestep is between start_step and end_step
cache_interval: interval of caching (1 means no caching)
cache_depth: depth of caching
'''

lewtun

# This is a modified version of TRL's `SFTTrainer` example (https://github.com/huggingface/trl/blob/main/examples/scripts/sft_trainer.py), 
# adapted to run with DeepSpeed ZeRO-3 and Mistral-7B-V1.0. The settings below were run on 1 node of 8 x A100 (80GB) GPUs.
#
# Usage:
#   - Install the latest transformers & accelerate versions: `pip install -U transformers accelerate`
#   - Install deepspeed: `pip install deepspeed==0.9.5`
#   - Install TRL from main: pip install git+https://github.com/huggingface/trl.git
#   - Clone the repo: git clone github.com/huggingface/trl.git
#   - Copy this Gist into trl/examples/scripts
#   - Run from root of trl repo with: accelerate launch --config_file=examples/accelerate_configs/deepspeed_zero3.yaml --gradient_accumulation_steps 8 examples/scripts/sft_trainer.py  

ritwikraha

Pretraining

---

A Map for Studying Pre-training in LLMs

• Data Collection
  • General Text Data
  • Specialized Data
• Data Preprocessing
  • Quality Filtering
• Deduplication

ollieatkinson

import Darwin
import Foundation
import UIKit

// https://github.com/xybp888/iOS-SDKs/blob/master/iPhoneOS17.1.sdk/System/Library/PrivateFrameworks/CoreSVG.framework/CoreSVG.tbd
// https://developer.limneos.net/index.php?ios=17.1&framework=UIKitCore.framework&header=UIImage.h

@objc
class CGSVGDocument: NSObject { }

aravindsrinivas

import functools
import numpy as np
import tensorflow.compat.v1 as tf
from tensorflow.python.tpu import tpu_function


BATCH_NORM_DECAY = 0.9
BATCH_NORM_EPSILON = 1e-5

tranquan

Overview

To setup some key bindings in Xcode with the same like VSCode

Add duplicate lines

Add this to /Applications/Xcode.app/Contents/Frameworks/IDEKit.framework/Versions/A/Resources/IDETextKeyBindingSet.plist Thanks to: https://gist.github.com/emotality/b1bcb2bb8a07921f9c8cad1c969daedf

<key>Duplication</key>