---
inference: false
language:
- ja
- en
license: llama2
tags:
- translation
---

# New Translation model released.

[C3TR-Adapter](https://huggingface.co./webbigdata/C3TR-Adapter) is the QLoRA adapter for google/gemma-7b.  
Despite the 4-bit quantization, the memory GPU requirement has increased to 8.1 GB. 
However, it is possible to run it with the free version of Colab and the performance is much improved!

# webbigdata/ALMA-7B-Ja-V2-GPTQ-Ja-En

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。  
ALMA-7B-Ja-V2 is a machine translation model that uses ALMA's learning method to translate Japanese to English.  

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。  
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.  

## サンプルコード

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。  
If you have a Google account, you can run it for free using the following Colab.  

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  
Click the "Open In Colab" button on the link to start Colab.  

[Free Colab Sample](https://github.com/webbigdata-jp/python_sample/blob/main/ALMA_7B_Ja_V2_GPTQ_Ja_En_Free_Colab_sample.ipynb)  

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。  
If you want to translate the entire file at once, try Colab below.  
[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)

以下のようなエラーが発生した場合は  
if you enconter error below.  

```RuntimeError: probability tensor contains either `inf`, `nan` or element < 0```  

It's mean your memory is not enough.  decrease your num_beams or token size or reduce target text length.  
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。  


## その他の版 Other Version

- 元のモデル [ALMA-7B-Ja-V2](https://huggingface.co./webbigdata/ALMA-7B-Ja-V2).
- original [ALMA-7B-Ja-V2](https://huggingface.co./webbigdata/ALMA-7B-Ja-V2).

## 本作業について about this work
- 本作業は[webbigdata](https://webbigdata.jp/)によって行われました 
- **This work was done by :** [webbigdata](https://webbigdata.jp/).


**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. 
Please find more details in their [paper](https://arxiv.org/abs/2309.11674).
```
@misc{xu2023paradigm,
      title={A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models}, 
      author={Haoran Xu and Young Jin Kim and Amr Sharaf and Hany Hassan Awadalla},
      year={2023},
      eprint={2309.11674},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
```

量子化設定　gptq 4bit/128G
Quantization settings gptq 4bit/128G