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license: cc-by-4.0
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---
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---
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license: cc-by-4.0
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language:
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- ja
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- en
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pipeline_tag: text-generation
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inference: false
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tags:
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- llama-2
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---
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日本語でtrainingしたllama2をinstruction用のデータセットでsftしたものになります
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base:
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https://huggingface.co/if001/llama2_ja_small
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trainingは以下のscript参照
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https://github.com/Lightning-AI/lit-gpt/tree/main
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## use
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("if001/sentencepiece_ja", trust_remote_code=True)
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model = AutoModelForCausalLM.from_pretrained("if001/llama2_ja_small")
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import torch
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from transformers import GenerationConfig
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instruct="東京でおすすめの観光地を教えてください。。"
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prompt=f"""以下は、タスクを説明する指示です。要求を適切に満たす応答を書きなさい。
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### 指示:
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{instruct}
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### 出力:
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"""
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inputs = tokenizer(prompt, return_tensors="pt")
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input_ids = inputs["input_ids"]
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generation_config = GenerationConfig(
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temperature=0.8,
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top_p=0.95,
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top_k=50,
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num_beams=1,
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do_sample=True,
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repetition_penalty=1.2,
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pad_token_id= tokenizer.pad_token_id,
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# pad_token_id=tokenizer.unk_token_id,
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eos_token_id=tokenizer.eos_token_id
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)
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with torch.no_grad():
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generation_output = model.generate(
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input_ids=input_ids,
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generation_config=generation_config,
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return_dict_in_generate=True,
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output_scores=True,
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max_new_tokens=64,
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)
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s = generation_output.sequences[0]
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output = tokenizer.decode(s)
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print(output)
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```
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出力
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```
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以下は、タスクを説明する指示です。要求を適切に満たす応答を書きなさい。
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### 指示:
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東京でおすすめの観光地を教えてください。。
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### 出力:
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- 東京で訪れる料理
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- 美術館
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- 博物館・新旧東の北京にある船浴場
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- モニュッキングスの4つの空き地
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- シュノーケリングチャイム、夜の奇抜な街
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- ツアーなど、芸術/建築の6つ
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```
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## dataset
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https://huggingface.co/datasets/kunishou/hh-rlhf-49k-ja
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https://huggingface.co/datasets/kunishou/databricks-dolly-15k-ja
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