Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
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DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
GUI for a Vocal Remover that uses Deep Neural Networks.
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
Open-source speech recognition toolkit for training, inference, streaming ASR, VAD, punctuation, speaker diarization pipelines, and OpenAI-compatible/MCP serving.
RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
A PyTorch-based Speech Toolkit
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
Fast and Accurate ML in 3 Lines of Code
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
Automatic architecture search and hyperparameter optimization for PyTorch
An autoML framework & toolkit for machine learning on graphs.
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.