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What is Petals?

The Petal tool is a decentralized platform that runs a large language model like Bloom-176b. It is capable of loading small parts of the model to run inference and fine-tuning. Single-batch inference takes approximately 1 second per step (token) and can run parallel inference up to hundreds of tokens/sec. This tool offers more than just a classic language model API, using fine-tune sampling methods and allowing users to execute custom paths and see hidden states. Petal also offers flexible PyTorch API. It is part of the BigScience research workshop project.

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⭐ Petals Core features

  • ✔️ Decentralized platform
  • ✔️ Large language model like bloom-176b
  • ✔️ Single-batch inference
  • ✔️ Fine-tuning
  • ✔️ Flexible pytorch api

⚙️ Petals use case ideas

  1. Natural language processing.
  2. Text generation.
  3. Sentiment analysis.

🙋‍♂️ Users of this tool

Ai researchers
Ml engineers
Nlp specialists
Data scientists
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❓ Petals FAQ

Petal is a decentralized platform that loads small parts of a large language model like Bloom-176b for single-batch inference and fine-tuning, with flexible PyTorch API.
Getting started with Petals is easy! Simply visit the official website and sign up for an account to start.
Petals uses a Waitlist pricing model
The typical users of Petals include:
  • Ai researchers
  • Ml engineers
  • Nlp specialists
  • Data scientists
Yes, Petals provides an API that developers can use to integrate its AI capabilities into their own applications.
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