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@@ -22,9 +22,21 @@ license: llama2
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  - [allenai/tulu-2-dpo-70b](https://huggingface.co/allenai/tulu-2-dpo-70b)
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  ## ライセンス
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- Llama2ライセンスを継承しますが、それ以外にもこのマージモデルはLlama2ライセンス以外のライセンスの影響を受けます。
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  - [allenai/tulu-2-dpo-70b](allenai/tulu-2-dpo-70b)の利用により、[AI2 ImpACT license](https://allenai.org/impact-license)を継承している可能性があります。ライセンスに関する連絡を受けた場合は変更の可能性があります。
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  ## ベンチマーク
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  ベースとしたkarakuri-lm-70b-chat-v0.1と本モデルの[japanese-mt-bench](https://github.com/Stability-AI/FastChat/tree/jp-stable/fastchat/llm_judge)の結果は以下の通りです。
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  (シングルターン, 4ビット量子化)
@@ -57,6 +69,17 @@ It utilizes the following two models:
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  While inheriting the Llama2 license, this merged model is also subject to other licenses due to its use of models beyond Llama2.
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  - Due to the use of [allenai/tulu-2-dpo-70b](allenai/tulu-2-dpo-70b), it may inherit the [AI2 ImpACT license](https://allenai.org/impact-license). I will change the license immediately if AI2 contacts me.
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  ## Benchmark
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  The results of this model and the base karakuri-lm-70b-chat-v0.1 on japanese-mt-bench are as follows.
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  (Single turn, 4-bit quantization)
 
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  - [allenai/tulu-2-dpo-70b](https://huggingface.co/allenai/tulu-2-dpo-70b)
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  ## ライセンス
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+ Llama2ライセンスを継承しますが、それ以外にもこのマージモデルは下記ライセンスの影響を受ける可能性があります。
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  - [allenai/tulu-2-dpo-70b](allenai/tulu-2-dpo-70b)の利用により、[AI2 ImpACT license](https://allenai.org/impact-license)を継承している可能性があります。ライセンスに関する連絡を受けた場合は変更の可能性があります。
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+ また、商用利用の際にはKARAKURI Incにコンタクトを取る必要があります。
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+ 元モデルのライセンスを引用します。
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+
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+ >Llama 2 is licensed under the LLAMA 2 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.
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+ >
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+ >Subject to the license above, and except for commercial purposes, you are free to share and adapt KARAKURI LM, provided that you must, in a recognizable and appropriate manner, (i) state that you are using KARAKURI LM developed by KARAKURI Inc., when you publish or make available to third parties KARAKURI LM, its derivative works or modification, or any output or results of KARAKURI LM or its derivative works or modification, and (ii) indicate your contributions, if you modified any material of KARAKURI LM.
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+ >
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+ >
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+ >If you plan to use KARAKURI LM for commercial purposes, please contact us beforehand. You are not authorized to use KARAKURI LM for commercial purposes unless we expressly grant you such rights.
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+ >
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+ >If you have any questions regarding the interpretation of above terms, please also feel free to contact us.
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+
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  ## ベンチマーク
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  ベースとしたkarakuri-lm-70b-chat-v0.1と本モデルの[japanese-mt-bench](https://github.com/Stability-AI/FastChat/tree/jp-stable/fastchat/llm_judge)の結果は以下の通りです。
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  (シングルターン, 4ビット量子化)
 
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  While inheriting the Llama2 license, this merged model is also subject to other licenses due to its use of models beyond Llama2.
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  - Due to the use of [allenai/tulu-2-dpo-70b](allenai/tulu-2-dpo-70b), it may inherit the [AI2 ImpACT license](https://allenai.org/impact-license). I will change the license immediately if AI2 contacts me.
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+ In addition, for commercial use, it is necessary to contact KARAKURI Inc. I will quote the license of the original model.
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+
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+ >Llama 2 is licensed under the LLAMA 2 Community License, Copyright © Meta Platforms, Inc. All Rights Reserved.
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+ >
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+ >Subject to the license above, and except for commercial purposes, you are free to share and adapt KARAKURI LM, provided that you must, in a recognizable and appropriate manner, (i) state that you are using KARAKURI LM developed by KARAKURI Inc., when you publish or make available to third parties KARAKURI LM, its derivative works or modification, or any output or results of KARAKURI LM or its derivative works or modification, and (ii) indicate your contributions, if you modified any material of KARAKURI LM.
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+ >
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+ >
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+ >If you plan to use KARAKURI LM for commercial purposes, please contact us beforehand. You are not authorized to use KARAKURI LM for commercial purposes unless we expressly grant you such rights.
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+ >
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+ >If you have any questions regarding the interpretation of above terms, please also feel free to contact us.
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+
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  ## Benchmark
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  The results of this model and the base karakuri-lm-70b-chat-v0.1 on japanese-mt-bench are as follows.
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  (Single turn, 4-bit quantization)