Popular GitHub Repositories for Mixture Of Gaussians

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.

? Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Elixir implementation of a LangChain style framework that lets Elixir projects integrate with and leverage LLMs.

? Lobe Chat - an open-source, modern-design AI chat framework. Supports Multi AI Providers( OpenAI / Claude 3 / Gemini / Ollama / DeepSeek / Qwen), Knowledge Base (file upload / knowledge management / RAG ), Multi-Modals (Plugins/Artifacts) and Thinking. One-click FREE deployment of your private ChatGPT/ Claude / DeepSeek application.

??? 60+ Implementations/tutorials of deep learning papers with side-by-side notes ?; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), ? reinforcement learning (ppo, dqn), capsnet, distillation, ... ?

Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)

Collection of awesome LLM apps with AI Agents and RAG using OpenAI, Anthropic, Gemini and opensource models.

100 Days of ML Coding

Port of OpenAI's Whisper model in C/C++

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

fabric is an open-source framework for augmenting humans using AI. It provides a modular framework for solving specific problems using a crowdsourced set of AI prompts that can be used anywhere.

Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.

? Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.

Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.

? Create, share, and use custom AI code assistants with our open-source IDE extensions and hub of models, rules, prompts, docs, and other building blocks

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.