Directory

YAML-configured open-source framework for fine-tuning and post-training LLMs: full, LoRA and QLoRA training, preference and RL methods, multimodal models and multi-GPU or multi-node runs

Hosting platform for open models, datasets and Spaces demo apps built on git repositories and Xet storage, with Inference Providers, Endpoints, Jobs and an open-source Python client and CLI

Python library for NumPy-style array computing with composable transformations (jit, grad, vmap, shard_map) compiled through XLA to CPU, GPU and TPU

Open-source deep-learning framework with eager tensors, autograd, torch.compile and distributed training, governed by the PyTorch Foundation and the base of most LLM tooling

Open-source Python framework for distributing tasks, actors and ML workloads across a cluster, with libraries for data processing, training, tuning, serving and reinforcement learning

Cloud platform for open-source models: serverless and dedicated inference, fine-tuning, GPU clusters, batch jobs and code sandboxes behind an OpenAI-compatible API

ML experiment tracking, sweeps, artifacts and model registry plus Weave for LLM tracing and evaluation, now sold by CoreWeave within its Forge platform with a free academic tier