Popular GitHub Repositories for Neural State Space Models

An Open Source Machine Learning Framework for Everyone

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

Tensors and Dynamic neural networks in Python with strong GPU acceleration

FULL v0, Cursor, Manus, Same.dev & Lovable System Prompts & AI Models.

为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, moss等。

Deep Learning for humans

??? 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, ... ?

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

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.

Deepfakes Software For All

Drag & drop UI to build your customized LLM flow

Making large AI models cheaper, faster and more accessible

Build and share delightful machine learning apps, all in Python. ? Star to support our work!

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

The Memory layer for AI Agents

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

:robot: The free, Open Source alternative to OpenAI, Claude and others. Self-hosted and local-first. Drop-in replacement for OpenAI, running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. Features: Generate Text, Audio, Video, Images, Voice Cloning, Distributed, P2P inference

? Industrial-strength Natural Language Processing (NLP) in Python