Where to Find Petals Documentation, Code, and Community Channels

Updated

Petals' official entry points are its website (petals.dev), a "Try now in Colab" link for a hands-on demo, "Docs on GitHub" for documentation and source code, and a Discord server or email subscription for development updates. The site also displays a live list of top contributors and network status, so you can check who is currently serving model parts before you join.

Official entry points

Resource What it gives you Where it lives
Website Project overview, supported models, speed figures, contributor list petals.dev
Colab notebook A runnable environment to try Petals without local setup "Try now in Colab" link on the homepage
GitHub docs Documentation and project code "Docs on GitHub" link on the homepage
Discord Community discussion and development updates Linked from the homepage
Email updates Occasional project news (the site says once every few months) Subscribe form on the homepage

What each channel is for

Trying it first: Colab

If you want to see Petals work before installing anything, the Colab link is the fastest path. The homepage describes generating text with Llama 3.1 (up to 405B), Mixtral (8x22B), Falcon (40B+), or BLOOM (176B) using a consumer-grade GPU or Google Colab. The intended flow is: you load part of the model, then join a network of people serving its other parts.

Reading and building: GitHub

The "Docs on GitHub" link is where you go for the actual documentation and source. This matters if you want more than the standard API surface — the site states you can use any fine-tuning and sampling methods, execute custom paths through the model, or inspect its hidden states, with the flexibility of PyTorch and 🤗 Transformers.

Following development: Discord and email

Discord is the live community channel. The email list is explicitly low-volume: the site says updates go out once every few months and that it only emails for "really exciting updates." Choose Discord if you want ongoing discussion, email if you only want occasional announcements.

Checking network health before you commit

The homepage includes a "Top contributors right now" section and a network status display. On the page as captured, the contributor list was still loading and the network status failed to load ("Oops, can't load the network status..."), so treat these as live widgets that may not always render — if they appear empty, that reflects the widget state, not necessarily the network.

Speed expectations from the site, useful when deciding whether the network suits your use case: single-batch inference runs at up to 6 tokens/sec for Llama 2 (70B) and up to 4 tokens/sec for Falcon (180B), which the project describes as enough for chatbots and interactive apps.

Practical notes

  • Petals is part of the BigScience research workshop, per the homepage.
  • The site does not state pricing or login requirements for these channels, so don't assume free access or no sign-up — check each destination directly.
  • If you plan to contribute compute rather than just consume it, the homepage offers a "Contribute my GPU" action alongside the contributor list.