Create README.md

README.md

@@ -0,0 +1,47 @@
+---
+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/).