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--- |
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license: apache-2.0 |
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datasets: |
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- SkelterLabsInc/JaQuAD |
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language: |
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- ja |
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--- |
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MambaSan-370m-instruct 🐍 |
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MambaSan-instruct is the first chat Japanese language model based on a state-space model architecture (Mamba). |
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The model is based on Albert Gu's and Tri Dao's work Mamba: Linear-Time Sequence Modeling with Selective State Spaces (paper) as well as their model implementation. This work was also inspired by heavenq's mamba-chat implementation in English. |
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Mamba-Chat is based on MambaSan-370m and was fine-tuned on 31,7k examples samples of the SkelterLabsInc/JaQuAD dataset. To learn more, you can: |
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- Take a look at the model on [Huggingface](https://huggingface.co/loiccabannes/MambaSan-370m-instruct) 🤗 |
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- Talk to Mamba-Chat on [Google Colab](https://colab.research.google.com/drive/1ZqHOC_RHU8ilAKreUMc_WNbo_melmNJX?usp=sharing) |
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The Code used for pretraining and finetuning will soon be published on my github: https://github.com/lcabannes |
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Citation |
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bibtex |
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@misc{lcabannes2024MambaSan-370m-instruct, |
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title = {MambaSan-370m-instruct}, |
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author = {Loïc Cabannes}, |
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year = {2024}, |
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howpublished = {HuggingFace}, |
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url = {https://huggingface.co/loiccabannes/MambaSan-370m-instruct/} |
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} |
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