Petals – Run LLMs at home, BitTorrent-style

Run large language models at home, BitTorrent‑style

• Generate text with Llama 3.1 (up to 405B), Mixtral (8x22B), Falcon (40B+) or BLOOM (176B)
  and fine‑tune them for your tasks — using a consumer-grade GPU or Google Colab.
• You load a part of the model, then join a
  network
  of people serving its other parts.
  Single‑batch inference runs at up to 6 tokens/sec for Llama 2 (70B) and
  up to 4 tokens/sec for Falcon (180B) — enough for
  chatbots and interactive apps.
• Beyond classic LLM 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 and 🤗 Transformers.

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This project is a part of the BigScience research workshop.