Update README.md

README.md

@@ -4,23 +4,36 @@ language:
 - ja
 - en
 ---
-# webbigdata/ALMA-7B-Ja-GPTQ-Ja-En
+# webbigdata/ALMA-7B-Ja-V2-GPTQ-Ja-En
 
-Original ALMA Model [ALMA-7B](https://huggingface.co/haoranxu/ALMA-7B). (26.95GB)  is a new paradigm translation model.  
+ALMA-7B-Ja-V2-GPTQ-Ja-En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-GPTQ-Ja-En is a machine translation model that uses ALMA's learning method to translate Japanese to English.  
 
-[ALMA-7B-Ja-V2-GPTQ-Ja-En](https://huggingface.co/webbigdata/ALMA-7B-Ja-V2-GPTQ-Ja-En) is a machine translation model that uses ALMA's learning method to translate Japanese to English.(13.3GB)  
+## サンプルコード
 
-This model is 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.   
+Googleアカウントをお持ちの方は以下のColabを使用して動かす事が出来ます。  
 
 [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)
 
-if you enconter error below.
+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.  
+これはメモリ不足を意味します。num_beamsかtoken sizeを減らしてください。  
+
+## その他の版 Other Version
+
+- None quantized model [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. 
@@ -34,7 +47,4 @@ Please find more details in their [paper](https://arxiv.org/abs/2309.11674).
       archivePrefix={arXiv},
       primaryClass={cs.CL}
 }
-```
-
-## about this work
-- **This work was done by :** [webbigdata](https://webbigdata.jp/).
+```