---
inference: false
language:
- ja
- en
- de
- is
- zh
- cs
---
# webbigdata/ALMA-7B-Ja

**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 our [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}
}
```

Original ALMA Model [ALMA-7B](https://huggingface.co/haoranxu/ALMA-7B). (26.95GB)  
https://huggingface.co/haoranxu/ALMA-7B

ALMA-7B-Ja is a machine translation model that uses ALMA's learning method to translate Japanese to English.(13.3GB)  

Like the original model, This model has been verified that it also has a translation function between the following languages, but if you want the translation function for these languages, it is better to use the original model.  

german and english  
Chinese and English  
Icelandic and English  
Czech and English  


[Sample Code For Free Colab](https://github.com/webbigdata-jp/python_sample/blob/main/ALMA_7B_Ja_Free_Colab_sample.ipynb)  

There is also a GPTQ quantized version model that reduces model size(3.9GB) and memory usage, although the performance is probably lower.  
And translation ability for languages other than Japanese and English has deteriorated significantly.   
[webbigdata/ALMA-7B-Ja-GPTQ-Ja-En](https://huggingface.co/webbigdata/ALMA-7B-Ja-GPTQ-Ja-En)  


## about this work
- **This work was done by :** [webbigdata](https://webbigdata.jp/).