Stars
A simplified and automated orchestration workflow to perform ML end-to-end (E2E) model tests and benchmarking on Cloud VMs across different frameworks.
A simple, performant and scalable Jax LLM!
Python best practices guidebook, written for humans.
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
A programming framework for agentic AI 🤖 PyPi: autogen-agentchat Discord: https://aka.ms/autogen-discord Office Hour: https://aka.ms/autogen-officehour
Generative Agents: Interactive Simulacra of Human Behavior
This repository contains a collection of papers and resources on Reasoning in Large Language Models.
Code and documentation to train Stanford's Alpaca models, and generate the data.
PyTorch implementation of MAE https//arxiv.org/abs/2111.06377
The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (V…
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
NVIDIA's Deep Imagination Team's PyTorch Library
Implementation of DALL-E 2, OpenAI's updated text-to-image synthesis neural network, in Pytorch
PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
A collection of resources and papers on Diffusion Models
GLIDE: a diffusion-based text-conditional image synthesis model
Assessing Humor in Edited News Headlines
(ෆ`꒳´ෆ) A Survey on Text-to-Image Generation/Synthesis.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
deep learning for image processing including classification and object-detection etc.
PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882
Learning OpenCV 4 Computer Vision with Python 3 – Third Edition, published by Packt
Machine Learning Resources, Practice and Research
Python code for "Probabilistic Machine learning" book by Kevin Murphy
"Probabilistic Machine Learning" - a book series by Kevin Murphy
Notes & exercise solutions of Part I from the book: "Hands-On ML with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems" by Aurelien Geron