🤝 Petals lets people run language models that are too large for one computer by using a distributed network with a BitTorrent-like approach.
Each participant loads part of the model on their GPU and connects to others serving the remaining parts. This makes it possible to use Llama 3.1, Mixtral, Falcon, or BLOOM from a consumer GPU or Google Colab.
The network supports interactive inference for chatbots and applications, but it is not limited to a traditional API. Users can also fine-tune models, change sampling methods, run custom paths, and inspect hidden states with PyTorch and Transformers.
🌐 The system broadens access to huge models, although it depends on enough participants and good connections between nodes. Contributing a GPU increases the capacity available to the entire community.
💡 Explanation in a nutshell#
Imagine splitting a huge book among many libraries. Each library stores some pages and, when someone wants to read it, they collaborate to provide the answer. Petals does something similar with an AI model: it distributes its layers among computers and coordinates the computation.
More information at the link 👇
