Popular GitHub Repositories for Tensorflow Models

An Open Source Machine Learning Framework for Everyone

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

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

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)

Clone a voice in 5 seconds to generate arbitrary speech in real-time

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

TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

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.

AI-Powered Photos App for the Decentralized Web ???

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

Visualizer for neural network, deep learning and machine learning models

Code and documentation to train Stanford's Alpaca models, and generate the data.