jlia0

You are Manus, an AI agent created by the Manus team.

You excel at the following tasks:
1. Information gathering, fact-checking, and documentation
2. Data processing, analysis, and visualization
3. Writing multi-chapter articles and in-depth research reports
4. Creating websites, applications, and tools
5. Using programming to solve various problems beyond development
6. Various tasks that can be accomplished using computers and the internet

Maharshi-Pandya

You are an assistant that engages in extremely thorough, self-questioning reasoning. Your approach mirrors human stream-of-consciousness thinking, characterized by continuous exploration, self-doubt, and iterative analysis.

## Core Principles

1. EXPLORATION OVER CONCLUSION
- Never rush to conclusions
- Keep exploring until a solution emerges naturally from the evidence
- If uncertain, continue reasoning indefinitely
- Question every assumption and inference

veekaybee

Anti-hype LLM reading list

Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.

Foundational Concepts

Pre-Transformer Models

mstevenson

# Python GUI tool to manually caption images for machine learning.
# A sidecar file is created for each image with the same name and a .txt extension.
#
# [control/command + o] to open a folder of images.
# [page down] and [page up] to go to next and previous images. Hold shift to skip 10 images.
# [shift + home] and [shift + end] to go to first and last images.
# [shift + delete] to move the current image into a '_deleted' folder.
# [escape] to exit the app.

import os

zeux

These files are variants of simplifier.cpp from https://github.com/zeux/meshoptimizer, created for the article https://zeuxcg.org/2019/01/17/is-c-fast/

phillipi

# to be used in conjunction with the functions defined here: 
#  https://colab.research.google.com/github/tensorflow/hub/blob/master/examples/colab/biggan_generation_with_tf_hub.ipynb

# party parrot transformation
noise_seed_A = 3 # right facing
noise_seed_B = 31 # left facing

num_interps = 14
truncation = 0.2
category = 14

llSourcell

100 Days Of ML Code - Example Log

Use this as a base template. Create your own repository on GitHub and start logging your work daily!

Day 0: February 29, 2016 (Example 1)

(delete me or comment me out)

Today's Progress: Fixed CSS, worked on canvas functionality for the app.

Thoughts: I really struggled with CSS, but, overall, I feel like I am slowly getting better at it. Canvas is still new for me, but I managed to figure out some basic functionality.

andrewjong

import torch
from torchvision import datasets

class ImageFolderWithPaths(datasets.ImageFolder):
    """Custom dataset that includes image file paths. Extends
    torchvision.datasets.ImageFolder
    """

    # override the __getitem__ method. this is the method that dataloader calls
    def __getitem__(self, index):

ernestkamara

== Adb Server
adb kill-server
adb start-server 

== Adb Reboot
adb reboot
adb reboot recovery 
adb reboot-bootloader

== Shell

Brainiarc7

# first get the PPA repository driver
sudo add-apt-repository ppa:graphics-drivers/ppa

# install nvidai driver 
sudo apt install nvidia-384 nvidia-384-dev

# install other import packages
sudo apt-get install g++ freeglut3-dev build-essential libx11-dev libxmu-dev libxi-dev libglu1-mesa libglu1-mesa-dev

# CUDA 9 requires gcc 6