most citedDistributed Inference and Fine-tuning of Large Language Models Over The Internet

14 citations · 20 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2023★ 14 cited

Distributed Inference and Fine-tuning of Large Language Models Over The Internet

Alexander Borzunov, Max Ryabinin, Artem Chumachenko +5

Large language models (LLMs) are useful in many NLP tasks and become more capable with size, with the best open-source models having over 50 billion parameters. However, using thes…

cs.LG2022★ 6 cited

Petals: Collaborative Inference and Fine-tuning of Large Models

Alexander Borzunov, Dmitry Baranchuk, Tim Dettmers +5

Many NLP tasks benefit from using large language models (LLMs) that often have more than 100 billion parameters. With the release of BLOOM-176B and OPT-175B, everyone can download…