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--- |
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library_name: transformers |
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license: apache-2.0 |
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language: |
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- ja |
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base_model: |
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- Qwen/Qwen2.5-32B-Instruct |
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pipeline_tag: text-generation |
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--- |
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## ABEJA-Qwen2.5-32b-Japanese-v0.1 |
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ABEJA-Qwen2.5-32b-Japanese-v0.1はQwen/Qwen2.5-32B-Instructをベースに日本語中心とした継続事前学習を実施したモデルです。 |
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Post-Traningはまだ実施しておらず、ChatVector(Qwen/Qwen2.5-32B-InstructとQwen/Qwen2.5-32B の差分ベクトル)により指示追従性能をあげています。 |
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詳細はABEJAのテックブログを参照してください。 |
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## 使い方 |
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```Python |
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import torch |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model_name = "abeja/ABEJA-Qwen2.5-32b-Japanese-v0.1" |
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model = AutoModelForCausalLM.from_pretrained( |
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model_name, |
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torch_dtype="auto", |
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device_map="auto" |
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) |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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prompt = "人とAIが協調するためには？" |
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messages = [ |
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{"role": "system", "content": "You are Qwen, created by Alibaba Cloud. You are a helpful assistant."}, |
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{"role": "user", "content": prompt} |
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] |
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text = tokenizer.apply_chat_template( |
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messages, |
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tokenize=False, |
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add_generation_prompt=True |
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) |
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device) |
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generated_ids = model.generate( |
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**model_inputs, |
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max_new_tokens=512 |
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) |
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generated_ids = [ |
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output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids) |
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] |
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response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0] |
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print(response) |
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``` |
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## 開発者 |
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- Hiroshi Kiyota |
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- Keisuke Fujimoto |
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- Kentaro Nakanishi |
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- Kyo Hattori |
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- Shinya Otani |
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- Shogo Muranushi |
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- Takuma Kume |
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- Tomoki Manabe |
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(*)アルファベット順 |
