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README.md
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---
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inference: false
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language:
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- ja
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- en
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---
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# webbigdata/ALMA-7B-Ja-GPTQ-Ja-En
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Original ALMA Model [ALMA-7B](https://huggingface.co/haoranxu/ALMA-7B). (26.95GB) is a new paradigm translation model.
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[ALMA-7B-Ja-GPTQ-Ja-En]](https://huggingface.co/webbigdata/ALMA-7B-Ja) is a machine translation model that uses ALMA's learning method to translate Japanese to English.(13.3GB)
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This model is GPTQ quantized version model that reduces model size(3.9GB) and memory usage, although the performance is probably lower.
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And translation ability for languages other than Japanese and English has deteriorated significantly.
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[Free Colab Sample](https://github.com/webbigdata-jp/python_sample/blob/main/ALMA_7B_Ja_GPTQ_Ja_En_Free_Colab_sample.ipynb)
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**ALMA** (**A**dvanced **L**anguage **M**odel-based tr**A**nslator) is an LLM-based translation model, which adopts a new translation model paradigm: it begins with fine-tuning on monolingual data and is further optimized using high-quality parallel data. This two-step fine-tuning process ensures strong translation performance.
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Please find more details in their [paper](https://arxiv.org/abs/2309.11674).
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```
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@misc{xu2023paradigm,
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title={A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models},
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author={Haoran Xu and Young Jin Kim and Amr Sharaf and Hany Hassan Awadalla},
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year={2023},
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eprint={2309.11674},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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## about this work
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- **This work was done by :** [webbigdata](https://webbigdata.jp/).
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