Instructions to use webbigdata/C3TR-Adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use webbigdata/C3TR-Adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/gemma-2-9b-it-bnb-4bit") model = PeftModel.from_pretrained(base_model, "webbigdata/C3TR-Adapter") - Notebooks
- Google Colab
- Kaggle
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README.md
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- [動作確認用の簡単なサンプル(A simple sample to check the operation)](https://github.com/webbigdata-jp/python_sample/blob/main/C3TR_Adapter_v2_Japanese_English_Translation_sample_code.ipynb)
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- [テキストファイルを一括で日英・英日翻訳するサンプル(Sample of batch translation of text files)](https://github.com/webbigdata-jp/python_sample/blob/main/C3TR_Adapter_v2_batch_translation_sample.ipynb)
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### モデルの動かし方(How to use Model)
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- [動作確認用の簡単なサンプル(A simple sample to check the operation)](https://github.com/webbigdata-jp/python_sample/blob/main/C3TR_Adapter_v2_Japanese_English_Translation_sample_code.ipynb)
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- [テキストファイルを一括で日英・英日翻訳するサンプル(Sample of batch translation of text files)](https://github.com/webbigdata-jp/python_sample/blob/main/C3TR_Adapter_v2_batch_translation_sample.ipynb)
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- [GPUがない環境でも動かす事ができるgguf版(A gguf version that can be run in environments without a GPU)](https://huggingface.co/webbigdata/C3TR-Adapter_gguf)
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### モデルの動かし方(How to use Model)
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