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README.md
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from transformers import TextStreamer, pipeline, AutoTokenizer, AutoModelForCausalLM
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import json
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model_id = 'spow12/
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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streamer = TextStreamer(tokenizer)
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ε»
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assistant: γ γ©γ΅γ‘: γγγγγγγγͺ
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```
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## Bias, Risks, and Limitations
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This model trained by japanese dataset included visual novel which contain nsfw content.
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```bibtex
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@misc {Visual-novel-transcriptor,
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author = { {YoungWoo Nam} },
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title = {
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year = 2024,
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url = { https://huggingface.co/spow12/Visual-novel-transcriptor },
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publisher = { Hugging Face }
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from transformers import TextStreamer, pipeline, AutoTokenizer, AutoModelForCausalLM
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import json
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model_id = 'spow12/Waifu_roleplaying_chatbot'
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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streamer = TextStreamer(tokenizer)
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assistant: γ γ©γ΅γ‘: γγγγγγγγͺ
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```
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To continue the conversation,
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```python
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message.append({
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'role': 'user',
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'content': """γ¦γΌγΆγΌ:γζ©γε¦ζ ‘θ‘γγγγγγγθ‘γγͺγγ¨ι
ε»γγ‘γγγγγ"""
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})
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out = pipe(message, **generation_configs)
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out
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```
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```output
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system: I want you to act like γ γ©γ΅γ‘ from SenrenBanka..
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....
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....
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....
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## Scene Background
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Conversation start at here.
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γ¦γΌγΆγΌ: γγγ―γγγγ γ©γ΅γ‘γγ
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assistant: γ γ©γ΅γ‘: γγγγδΈ»δΊΊ
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user: γ¦γΌγΆγΌ:γζ©γε¦ζ ‘θ‘γγγγγγγθ‘γγͺγγ¨ι
ε»γγ‘γγγγγ
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assistant: γ γ©γ΅γ‘: γγγγγγγγͺ
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```
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## Bias, Risks, and Limitations
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This model trained by japanese dataset included visual novel which contain nsfw content.
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```bibtex
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@misc {Visual-novel-transcriptor,
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author = { {YoungWoo Nam} },
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title = { Waifu_roleplaying_chatbot },
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year = 2024,
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url = { https://huggingface.co/spow12/Visual-novel-transcriptor },
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publisher = { Hugging Face }
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