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Alexander Borzunov
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2020 – today
- 2024
- [c7]Tim Dettmers, Ruslan Svirschevski, Vage Egiazarian, Denis Kuznedelev, Elias Frantar, Saleh Ashkboos, Alexander Borzunov, Torsten Hoefler, Dan Alistarh:
SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression. ICLR 2024 - 2023
- [c6]Alexander Borzunov, Dmitry Baranchuk, Tim Dettmers, Maksim Riabinin, Younes Belkada, Artem Chumachenko, Pavel Samygin, Colin Raffel:
Petals: Collaborative Inference and Fine-tuning of Large Models. ACL (demo) 2023: 558-568 - [c5]Max Ryabinin, Tim Dettmers, Michael Diskin, Alexander Borzunov:
SWARM Parallelism: Training Large Models Can Be Surprisingly Communication-Efficient. ICML 2023: 29416-29440 - [c4]Alexander Borzunov, Max Ryabinin, Artem Chumachenko, Dmitry Baranchuk, Tim Dettmers, Younes Belkada, Pavel Samygin, Colin A. Raffel:
Distributed Inference and Fine-tuning of Large Language Models Over The Internet. NeurIPS 2023 - [i7]Max Ryabinin, Tim Dettmers, Michael Diskin, Alexander Borzunov:
SWARM Parallelism: Training Large Models Can Be Surprisingly Communication-Efficient. CoRR abs/2301.11913 (2023) - [i6]Tim Dettmers, Ruslan Svirschevski, Vage Egiazarian, Denis Kuznedelev, Elias Frantar, Saleh Ashkboos, Alexander Borzunov, Torsten Hoefler, Dan Alistarh:
SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression. CoRR abs/2306.03078 (2023) - [i5]Alexander Borzunov, Max Ryabinin, Artem Chumachenko, Dmitry Baranchuk, Tim Dettmers, Younes Belkada, Pavel Samygin, Colin Raffel:
Distributed Inference and Fine-tuning of Large Language Models Over The Internet. CoRR abs/2312.08361 (2023) - 2022
- [c3]Eduard Gorbunov, Alexander Borzunov, Michael Diskin, Max Ryabinin:
Secure Distributed Training at Scale. ICML 2022: 7679-7739 - [i4]Alexander Borzunov, Max Ryabinin, Tim Dettmers, Quentin Lhoest, Lucile Saulnier, Michael Diskin, Yacine Jernite, Thomas Wolf:
Training Transformers Together. CoRR abs/2207.03481 (2022) - [i3]Alexander Borzunov, Dmitry Baranchuk, Tim Dettmers, Max Ryabinin, Younes Belkada, Artem Chumachenko, Pavel Samygin, Colin Raffel:
Petals: Collaborative Inference and Fine-tuning of Large Models. CoRR abs/2209.01188 (2022) - 2021
- [c2]Alexander Borzunov, Max Ryabinin, Tim Dettmers, Quentin Lhoest, Lucile Saulnier, Michael Diskin, Yacine Jernite, Thomas Wolf:
Training Transformers Together. NeurIPS (Competition and Demos) 2021: 335-342 - [c1]Michael Diskin, Alexey Bukhtiyarov, Max Ryabinin, Lucile Saulnier, Quentin Lhoest, Anton Sinitsin, Dmitry Popov, Dmitry V. Pyrkin, Maxim Kashirin, Alexander Borzunov, Albert Villanova del Moral, Denis Mazur, Ilia Kobelev, Yacine Jernite, Thomas Wolf, Gennady Pekhimenko:
Distributed Deep Learning In Open Collaborations. NeurIPS 2021: 7879-7897 - [i2]Michael Diskin, Alexey Bukhtiyarov, Max Ryabinin, Lucile Saulnier, Quentin Lhoest, Anton Sinitsin, Dmitry Popov, Dmitry V. Pyrkin, Maxim Kashirin, Alexander Borzunov, Albert Villanova del Moral, Denis Mazur, Ilia Kobelev, Yacine Jernite, Thomas Wolf, Gennady Pekhimenko:
Distributed Deep Learning in Open Collaborations. CoRR abs/2106.10207 (2021) - [i1]Eduard Gorbunov, Alexander Borzunov, Michael Diskin, Max Ryabinin:
Secure Distributed Training at Scale. CoRR abs/2106.11257 (2021)
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