| 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 | 377 | 2023 |
| 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 | 117 | 2023 |
| 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, 12312-12331, 2023 | 103 | 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 | 84 | 2021 |
| 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 | 67 | 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 | 24 | 2022 |
| 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 | 17 | 2022 |
| Swarm parallelism: Training large models can be surprisingly communication-efficient, 2023 M Ryabinin, T Dettmers, M Diskin, A Borzunov URL https://arxiv. org/abs/2301.11913, 0 | 5 | |
Tim DettmersAllen Institute for AI; Carnegie Mellon UniversityVerified email at allenai.org
