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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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license: llama2 |
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tags: |
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- translation |
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--- |
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# New Translation model released. |
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[C3TR-Adapter](https://huggingface.co/webbigdata/C3TR-Adapter) is the QLoRA adapter for google/gemma-7b. |
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Despite the 4-bit quantization, the memory GPU requirement has increased to 8.1 GB. |
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However, it is possible to run it with the free version of Colab and the performance is much improved! |
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# webbigdata/ALMA-7B-Ja-V2-GPTQ-Ja-En |
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ALMA-7B-Ja-V2は日本語から英語、英語から日本語への機械翻訳を行うモデルです。 |
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ALMA-7B-Ja-V2 is a machine translation model that uses ALMA's learning method to translate Japanese to English. |
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ALMA-7B-Ja-V2-GPTQ-Ja-Enは量子化、つまり多少の性能は落ちますがサイズを小さくし、実行速度を早くし、使いやすくした版です。 |
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ALMA-7B-Ja-V2-GPTQ-Ja-En is a quantized version, i.e., it is smaller in size, faster in execution, and easier to use, with some performance loss. |
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## サンプルコード |
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Googleアカウントをお持ちの方は以下のColabを使用して無料で動かす事が出来ます。 |
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If you have a Google account, you can run it for free using the following Colab. |
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リンク先で「Open In Colab」ボタンを押してColabを起動してください |
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Click the "Open In Colab" button on the link to start Colab. |
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[Free Colab Sample](https://github.com/webbigdata-jp/python_sample/blob/main/ALMA_7B_Ja_V2_GPTQ_Ja_En_Free_Colab_sample.ipynb) |
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テキストファイル全体を一気に翻訳したい方は、以下のColabをお試しください。 |
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If you want to translate the entire file at once, try Colab below. |
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[ALMA_7B_Ja_V2_GPTQ_Ja_En_batch_translation_sample](https://github.com/webbigdata-jp/python_sample/blob/main/ALMA_7B_Ja_V2_GPTQ_Ja_En_batch_translation_sample.ipynb) |
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以下のようなエラーが発生した場合は |
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if you enconter error below. |
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```RuntimeError: probability tensor contains either `inf`, `nan` or element < 0``` |
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It's mean your memory is not enough. decrease your num_beams or token size or reduce target text length. |
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これはメモリ不足を意味します。num_beamsかtoken size、もしくは翻訳対象の文の長さを減らしてください。 |
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## その他の版 Other Version |
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- 元のモデル [ALMA-7B-Ja-V2](https://huggingface.co/webbigdata/ALMA-7B-Ja-V2). |
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- original [ALMA-7B-Ja-V2](https://huggingface.co/webbigdata/ALMA-7B-Ja-V2). |
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## 本作業について about this work |
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- 本作業は[webbigdata](https://webbigdata.jp/)によって行われました |
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- **This work was done by :** [webbigdata](https://webbigdata.jp/). |
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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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量子化設定 gptq 4bit/128G |
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Quantization settings gptq 4bit/128G |
