Run 100B+ language models at home, BitTorrent‑style

  • Run large language models like BLOOM-176B collaboratively — you load a small part of the model, then team up with people serving the other parts to run inference or fine-tuning.
  • Single-batch inference runs at ≈ 1 sec per step (token) — up to 10x faster than offloading, enough for chatbots and other interactive apps. Parallel inference reaches hundreds of tokens/sec.
  • Beyond classic language model APIs — you can employ any fine-tuning and sampling methods, execute custom paths through the model, or see its hidden states. You get the comforts of an API with the flexibility of PyTorch.

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This project is a part of the BigScience research workshop.