Popular GitHub Repositories for Model Based Systems Engineering

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

Dify is an open-source LLM app development platform. Dify's intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.

21 Lessons, Get Started Building with Generative AI ? https://microsoft.github.io/generative-ai-for-beginners/

For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.

RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.

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

? Guides, papers, lecture, notebooks and resources for prompt engineering

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

A high-throughput and memory-efficient inference and serving engine for LLMs

1 min voice data can also be used to train a good TTS model! (few shot voice cloning)

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

?? - a deep learning toolkit for Text-to-Speech, battle-tested in research and production

Learn how to design, develop, deploy and iterate on production-grade ML applications.

Making large AI models cheaper, faster and more accessible

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

OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.

A generative speech model for daily dialogue.

Langchain-Chatchat（原Langchain-ChatGLM）基于 Langchain 与 ChatGLM, Qwen 与 Llama 等语言模型的 RAG 与 Agent 应用 | Langchain-Chatchat (formerly langchain-ChatGLM), local knowledge based LLM (like ChatGLM, Qwen and Llama) RAG and Agent app with langchain

Instant voice cloning by MIT and MyShell. Audio foundation model.

Easily train a good VC model with voice data <= 10 mins!