Stable LM 2 1.6B Technical Report
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arXiv
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| Autori principali: | , , , , , , , , , , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| author | Bellagente, Marco Tow, Jonathan Mahan, Dakota Phung, Duy Zhuravinskyi, Maksym Adithyan, Reshinth Baicoianu, James Brooks, Ben Cooper, Nathan Datta, Ashish Lee, Meng Mostaque, Emad Pieler, Michael Pinnaparju, Nikhil Rocha, Paulo Saini, Harry Teufel, Hannah Zanichelli, Niccolo Riquelme, Carlos |
| author_facet | Bellagente, Marco Tow, Jonathan Mahan, Dakota Phung, Duy Zhuravinskyi, Maksym Adithyan, Reshinth Baicoianu, James Brooks, Ben Cooper, Nathan Datta, Ashish Lee, Meng Mostaque, Emad Pieler, Michael Pinnaparju, Nikhil Rocha, Paulo Saini, Harry Teufel, Hannah Zanichelli, Niccolo Riquelme, Carlos |
| contents | We introduce StableLM 2 1.6B, the first in a new generation of our language model series. In this technical report, we present in detail the data and training procedure leading to the base and instruction-tuned versions of StableLM 2 1.6B. The weights for both models are available via Hugging Face for anyone to download and use. The report contains thorough evaluations of these models, including zero- and few-shot benchmarks, multilingual benchmarks, and the MT benchmark focusing on multi-turn dialogues. At the time of publishing this report, StableLM 2 1.6B was the state-of-the-art open model under 2B parameters by a significant margin. Given its appealing small size, we also provide throughput measurements on a number of edge devices. In addition, we open source several quantized checkpoints and provide their performance metrics compared to the original model. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_17834 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Stable LM 2 1.6B Technical Report Bellagente, Marco Tow, Jonathan Mahan, Dakota Phung, Duy Zhuravinskyi, Maksym Adithyan, Reshinth Baicoianu, James Brooks, Ben Cooper, Nathan Datta, Ashish Lee, Meng Mostaque, Emad Pieler, Michael Pinnaparju, Nikhil Rocha, Paulo Saini, Harry Teufel, Hannah Zanichelli, Niccolo Riquelme, Carlos Computation and Language Machine Learning We introduce StableLM 2 1.6B, the first in a new generation of our language model series. In this technical report, we present in detail the data and training procedure leading to the base and instruction-tuned versions of StableLM 2 1.6B. The weights for both models are available via Hugging Face for anyone to download and use. The report contains thorough evaluations of these models, including zero- and few-shot benchmarks, multilingual benchmarks, and the MT benchmark focusing on multi-turn dialogues. At the time of publishing this report, StableLM 2 1.6B was the state-of-the-art open model under 2B parameters by a significant margin. Given its appealing small size, we also provide throughput measurements on a number of edge devices. In addition, we open source several quantized checkpoints and provide their performance metrics compared to the original model. |
| title | Stable LM 2 1.6B Technical Report |
| topic | Computation and Language Machine Learning |
| url | https://arxiv.org/abs/2402.17834 |