Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
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Updated
Jun 12, 2024 - Python
PyTorch is an open source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing, primarily developed by Facebook's AI Research lab.
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
LLM training code for Databricks foundation models
PyTorch/XLA integration with JetStream (https://github.com/google/JetStream) for LLM inference"
Vanilla Recurrent Neural Network Implemented from Scratch in PyTorch
Serve, optimize and scale PyTorch models in production
A retargetable MLIR-based machine learning compiler and runtime toolkit.
Deep Learning for humans
Package to holographically generate light potentials of arbitrary shape using a phase-modulating spatial light modulator (SLM).
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
A codebase dedicated to exploring multimodal learning approaches by integrating images of host galaxies of supernovae and their corresponding light-curves and spectra.
A high-throughput and memory-efficient inference and serving engine for LLMs
Decentralized deep learning in PyTorch. Built to train models on thousands of volunteers across the world.
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
A Framework to streamline the research of seq2seq models
Multi-LoRA inference server that scales to 1000s of fine-tuned LLMs
Object Detection and Semantic Segmentation using PyTorch
Created by Facebook's AI Research lab (FAIR)
Released September 2016
Latest release 14 days ago