Artem Chumachenko
AI Engineer at Together AI
Amsterdam, North Holland, Netherlands
Summary
🤩
Rockstar🎓
Top SchoolArtem Chumachenko is an AI Engineer based in Amsterdam with 9 years of experience building and deploying large language models and dialog systems. He has driven model training and finetuning work at Yandex (YaLM up to 14B) and improved chatbot personalization at Neiro.ai, and now applies that expertise at Together AI. His open-source contributions to the well-known BigScience "petals" project added distributed generation, beam search, sampling and adapter/prefix-tuning support—enabling BitTorrent-style LLM inference and faster fine-tuning. With a research background from MIPT in model compression for transformers, he uniquely blends efficiency-focused research with production-grade generative systems.
10 years of coding experience
4 years of employment as a software developer
Bachelor's degree, Applied Physics and Mathematics, Bachelor's degree, Applied Physics and Mathematics at Moscow Institute of Physics and Technology (State University) (MIPT)
Github Skills (15)
pytorch10
machine-learning10
transformer10
language-models10
nlp10
language-model10
python10
distributed-system9
large-language-model9
large-language-models9
distributed-systems9
gpt9
deep-learning9
mixture7
mixtures7
Programming languages (4)
Github contributions (5)
bigscience-workshop/petals
Jun 2022 - Jan 2023
🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
Role in this project:
ML Engineer
ML EngineerContributions:30 reviews, 97 commits, 40 PRs in 6 months
Contributions summary:Artem primarily contributed to the development of a distributed language model platform, specifically focusing on integrating generation capabilities within the `petals` framework. Their contributions include implementing a `RemoteGenerationMixin` class for auto-regressive text generation, adding support for various decoding algorithms such as greedy search and sampling, and integrating prefix-tuned inference. The user also introduced the `beam_search` algorithm and designed functionality for utilizing adapters. Their work directly impacts the models capabilities for generation tasks.
llama2finetuningbittorrentllamahuggingface-transformers
catalyst-team/dl-course
Sep 2020 - Dec 2020
Deep Learning with Catalyst
Contributions:68 commits, 47 PRs, 47 pushes in 3 months
deep-learningcatalystmachine-learning
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