Papers by Dmitry Baranchuk

1 papers
Petals: Collaborative Inference and Fine-tuning of Large Models (2023.acl-demo)

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Challenge: Recent studies show that pretrained language models can solve practical tasks using more than 100 billion parameters.
Approach: They propose a system for inference and fine-tuning of large models collaboratively by joining the resources of multiple parties.
Outcome: The proposed system outperforms offloading for very large models running on consumer GPUs with 1 step per second, enough for many interactive LLM applications.

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