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# Model Card for Model ID

gemma-2-9b-it quantized with imatrix containing a lot of Japanese text  
日本語テキストを多く含むimatrixで量子化されたgemma-2-9b-it  

## Model Details

It is known that using imatrix when quantizing a model for llama.cpp improves performance.  
However, imatrix is often created only from English text. In cases where a model is used in languages other than English, wouldn't it be better to create an imatrix by mixing text in other languages?  
This page confirms the effectiveness of multilingual imatrix.

モデルをllama.cpp用に量子化する際にimatrixを使うと性能が向上する事が知られています。  
しかし、imatrixは英語テキストのみから作成されている事が多いです。英語以外の言語を使ってモデルを使用するケースでは他の言語のテキストも混ぜてimatrixを作成した方がよいのではないでしょうか？  
本ページは多言語版imatrixの有効性を確かめました。  

### Model Description


![wiki.test.raw_perplexity_score.png](wiki.test.raw_perplexity_score.png)


![ja-wiki.test.raw_perplexity_score.png](ja-wiki.test.raw_perplexity_score.png)



#### Terminology

wiki.test.raw score  
Perplexity Score measured using wiki.test.raw published by Salesforce and the llama-perplexity command with -c 512 setting.  

ja-wiki.test.raw perplexity score  
Perplexity score measured in the same way using Japanese data ([ja-wiki.test.raw]()) with the same file size as wiki.test.raw, extracted from a Japanese wiki.  



Bartowski model  
[Bartowski](https://huggingface.co/bartowski) is a person who has quantized many models and contributed to the community. He creates imatrix from English-only data[calibration_datav3.txt](https://gist.github.com/bartowski1182/eb213dccb3571f863da82e99418f81e8).  

Imatrix-jpn-test model  
This model. Its created with the multilingual version of text[calibration_datav3_plus_jpn_v1.txt](https://huggingface.co/dahara1/imatrix-jpn-test/blob/main/calibration_datav3_plus_jpn_v1.txt).




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