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--- |
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license: cc-by-nc-4.0 |
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--- |
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## License |
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非商用ライセンスで公開します。 |
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## Chat Vector |
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``` |
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Tora-7B-v0.1 = NTQAI/chatntq-ja-7b-v1.0 + (openchat/openchat-3.5-0106 - mistralai/Mistral-7B-v0.1) |
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``` |
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## 実装 |
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@jovyan様の実装を参考に下記のコードでモデルを作成しました。 |
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```python |
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import torch |
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from transformers import AutoModelForCausalLM |
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def build_chat_vector_model( |
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base_model_name, |
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inst_model_name, |
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target_model_name, |
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skip_layers, |
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): |
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base_model = AutoModelForCausalLM.from_pretrained( |
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base_model_name, |
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torch_dtype=torch.bfloat16, |
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device_map="cpu", |
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) |
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inst_model = AutoModelForCausalLM.from_pretrained( |
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inst_model_name, |
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torch_dtype=torch.bfloat16, |
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device_map="cpu", |
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) |
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target_model = AutoModelForCausalLM.from_pretrained( |
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target_model_name, |
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torch_dtype=torch.bfloat16, |
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device_map="cuda", |
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) |
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# 英語ベースモデル |
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for k, v in base_model.state_dict().items(): |
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print(k, v.shape) |
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# 日本語継続事前学習モデル |
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for k, v in target_model.state_dict().items(): |
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print(k, v.shape) |
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# 除外対象 |
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skip_layers = ["model.embed_tokens.weight", "lm_head.weight"] |
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for k, v in target_model.state_dict().items(): |
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# layernormも除外 |
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if (k in skip_layers) or ("layernorm" in k): |
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continue |
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chat_vector = inst_model.state_dict()[k] - base_model.state_dict()[k] |
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new_v = v + chat_vector.to(v.device) |
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v.copy_(new_v) |
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target_model.save_pretrained("./chat_model") |
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return |
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if __name__ == '__main__': |
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base_model_name = "mistralai/Mistral-7B-v0.1" |
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inst_model_name = "openchat/openchat-3.5-0106" |
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target_model_name = "NTQAI/chatntq-ja-7b-v1.0" |
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skip_layers = ["model.embed_tokens.weight", "lm_head.weight"] |
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build_chat_vector_model( |
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base_model_name=base_model_name, |
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inst_model_name=inst_model_name, |
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target_model_name=target_model_name, |
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skip_layers=skip_layers |
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) |
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``` |
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## ベンチマーク (Japanese MT bench) |
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- single turnのみ評価 |
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|model|category|score|ver| |
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|:---|:---|:---|:---| |
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|Tora-7B-v0.1|Writing|5.4|single-turn| |
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|Tora-7B-v0.1|Roleplay|6.6|single-turn| |
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|Tora-7B-v0.1|Reasoning|7.3|single-turn| |
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|Tora-7B-v0.1|Math|3.5|single-turn| |
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|Tora-7B-v0.1|Coding|4.7|single-turn| |
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|Tora-7B-v0.1|Extraction|6.3|single-turn| |
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|Tora-7B-v0.1|STEM|7.2|single-turn| |
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|Tora-7B-v0.1|Humanities|8.5|single-turn| |
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## ベンチマーク (Nejumi leaderboard) |
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- runs.summary["mtbench_leaderboard_table"]の結果を転記 |
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|model|category|score| |
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|:---|:---|:---| |
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|Tora-7B-v0.1|Writing|7.55| |
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|Tora-7B-v0.1|Roleplay|7.5| |
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|Tora-7B-v0.1|Reasoning|4.35| |
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|Tora-7B-v0.1|Math|2.95| |
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|Tora-7B-v0.1|Coding|3.7| |
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|Tora-7B-v0.1|Extraction|7.0| |
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|Tora-7B-v0.1|STEM|7.85| |
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|Tora-7B-v0.1|Humanities|9.65| |
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|Tora-7B-v0.1|AVG_mtbench|6.319| |
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- runs.summary["jaster_radar_table"]の結果を転記 |
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|model|category|score| |
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|:---|:---|:---| |
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|Tora-7B-v0.1|NLI|0.588| |
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|Tora-7B-v0.1|QA|0.1708| |
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|Tora-7B-v0.1|RC|0.798| |
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|Tora-7B-v0.1|MC|0.25| |
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|Tora-7B-v0.1|EL|0.0| |
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|Tora-7B-v0.1|FA|0.1359| |
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|Tora-7B-v0.1|MR|0.2| |
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## 謝辞 |
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ChatVectorの記事を執筆してくださった@jovyan様に深くお礼申し上げます。 |
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## 参考 |
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[Chat Vectorを使って日本語LLMをチャットモデルに改造する](https://qiita.com/jovyan/items/ee6affa5ee5bdaada6b4) |
