| SpQR: A sparse-quantized representation for near-lossless llm weight compression T Dettmers, R Svirschevski, V Egiazarian, D Kuznedelev, E Frantar, ... International Conference on Learning Representations (ICLR) 2024, 2023 | 63 | 2023 |
| Distributed deep learning in open collaborations M Diskin, A Bukhtiyarov, M Ryabinin, L Saulnier, A Sinitsin, D Popov, ... Advances in Neural Information Processing Systems 34, 7879-7897, 2021 | 37 | 2021 |
| Petals: Collaborative inference and fine-tuning of large models A Borzunov, D Baranchuk, T Dettmers, M Ryabinin, Y Belkada, ... Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023 | 29 | 2023 |
| Secure distributed training at scale E Gorbunov, A Borzunov, M Diskin, M Ryabinin Proceedings of the 39th International Conference on Machine Learning 162 …, 2022 | 13 | 2022 |
| SWARM Parallelism: Training Large Models Can Be Surprisingly Communication-Efficient M Ryabinin, T Dettmers, M Diskin, A Borzunov Proceedings of the 40th International Conference on Machine Learning, PMLR …, 2023 | 11 | 2023 |
| Training transformers together A Borzunov, M Ryabinin, T Dettmers, Q Lhoest, L Saulnier, M Diskin, ... Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track 176 …, 2022 | 9 | 2022 |
| Distributed Inference and Fine-tuning of Large Language Models Over The Internet A Borzunov, M Ryabinin, A Chumachenko, D Baranchuk, T Dettmers, ... Advances in Neural Information Processing Systems 36, 2024 | 7 | 2024 |
Max RyabininTogether AIVerified email at together.ai
