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--- |
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license: mit |
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language: |
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- ja |
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pipeline_tag: text-generation |
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base_model: |
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- sbintuitions/sarashina2.2-0.5b |
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--- |
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# sbintuitions/sarashina2.2-0.5b-instruct-v0.1 |
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## Model Summary |
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This repository provides Japanese language models trained by [SB Intuitions](https://www.sbintuitions.co.jp/). |
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## Model Details |
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- Model type: Autoregressive Language Model |
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- Language(s): Japanese |
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## How to use |
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```python |
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import torch |
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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline, set_seed |
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# モデルのロード |
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model_name = "sbintuitions/sarashina2.2-0.5b-instruct-v0.1" |
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model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto") |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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chat_pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer) |
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set_seed(123) |
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# ユーザーの入力 |
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user_input = [{"role": "user", "content": "こんにちは。あなたの名前を教えて"}] |
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# モデルによる応答生成 |
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responses = chat_pipeline( |
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user_input, |
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max_length=50, |
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do_sample=True, |
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num_return_sequences=3, |
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) |
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# 応答を表示 |
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for i, response in enumerate(responses, 1): |
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print(f"Response {i}: {response['generated_text']}") |
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# Response 1: [{'role': 'user', 'content': 'こんにちは。あなたの名前を教えて'}, {'role': 'assistant', 'content': 'Sarashina2と言います。本日のご要件を教えて下さい。'}] |
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# Response 2: [{'role': 'user', 'content': 'こんにちは。あなたの名前を教えて'}, {'role': 'assistant', 'content': 'こんにちは!私の名前はSarashina2です。今日はどうしましたか?'}] |
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# Response 3: [{'role': 'user', 'content': 'こんにちは。あなたの名前を教えて'}, {'role': 'assistant', 'content': 'Sarashina2と言います。本日のご要件を教えて下さい。'}] |
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``` |
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## Limitations |
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This model has limited safety training. |
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Therefore, it might generate some meaningless sequences, some inaccurate instances, or biased/objectionable outputs. |
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Before using it, we would like developers to tune models based on human preferences and safety considerations. |
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## License |
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MIT License |
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