Popular GitHub Repositories for Semantic Data Model

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

Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.

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.

Deep Learning for humans

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

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

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

A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications.

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

? Turn entire websites into LLM-ready markdown or structured data. Scrape, crawl and extract with a single API.

LlamaIndex is the leading framework for building LLM-powered agents over your data.

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.

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.