Stars
🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Collection of Summer 2026 tech internships!
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
We write your reusable computer vision tools. 💜
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
⚡ A Fast, Extensible Progress Bar for Python and CLI
Open-sourced codes for MiniGPT-4 and MiniGPT-v2 (https://minigpt-4.github.io, https://minigpt-v2.github.io/)
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Code samples for my book "Neural Networks and Deep Learning"
Python composable command line interface toolkit
🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org
High-Resolution 3D Assets Generation with Large Scale Hunyuan3D Diffusion Models.
Minimal reproduction of DeepSeek R1-Zero
pix2code: Generating Code from a Graphical User Interface Screenshot
Refine high-quality datasets and visual AI models
Source code for Twitter's Recommendation Algorithm
Script for downloading Coursera.org videos and naming them.
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
Easily fine-tune, evaluate and deploy gpt-oss, Qwen3, DeepSeek-R1, or any open source LLM / VLM!
Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
High-quality multi-lingual text-to-speech library by MyShell.ai. Support English, Spanish, French, Chinese, Japanese and Korean.
📚 Parameterize, execute, and analyze notebooks
[NeurIPS 2023] Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
This repository contains my personal notes and summaries on DeepLearning.ai specialization courses. I've enjoyed every little bit of the course hope you enjoy my notes too.