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maomao88
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Model Details
Model Provider
maomao88
Model Tree
mistralai/Mistral-7B-Instruct-v0.1
Input Modalities
Output Modalities
Supported Functionality
This repository contains a LoRA adapter trained with the maomao88/anime-waifu-personality-chat-with-questions dataset via Supervised Fine-Tuning (SFT) to add anime-style personalities to the Mistral-7B-Instruct model.
The personalities supported are:
You can load this adapter with the following code:
text
from transformers import AutoModelForCausalLMfrom peft import PeftModelfrom transformers import AutoTokenizerimport torch base_model = AutoModelForCausalLM.from_pretrained( "mistralai/Mistral-7B-Instruct-v0.1") tokenizer = AutoTokenizer.from_pretrained( "mistralai/Mistral-7B-Instruct-v0.1") model = PeftModel.from_pretrained( base_model, "maomao88/anime-waifu-mistral-lora") def chat_with_personality(trait, user_input, max_new_tokens=100, temperature=0.8): """ Generate a response from the fine-tuned model using a given personality trait. """ messages = [ { "role": "system", "content": f"You are an anime character with the following personality: {trait}." }, { "role": "user", "content": user_input } ] # Apply Mistral's chat template prompt = tokenizer.apply_chat_template( messages, tokenize=False, add_generation_prompt=True ) inputs = tokenizer(prompt, return_tensors="pt").to(model.device) with torch.no_grad(): outputs = model.generate( **inputs, max_new_tokens=max_new_tokens, do_sample=True, temperature=temperature, top_p=0.9, pad_token_id=tokenizer.eos_token_id, repetition_penalty=1.1 ) # Decode only the generated text portion (skip <s> etc.) response = tokenizer.decode(outputs[0], skip_special_tokens=True) # Remove the prompt portion to keep only the assistant reply if "[/INST]" in response: response = response.split("[/INST]")[-1].strip() return response chat_with_personality("tsundere", "What do you think of the moon?") # Response Example: It’s not like I care about the moon or anything… but it sure is pretty tonight!The anime characters supported are as follows:
from transformers import AutoModelForCausalLMfrom peft import PeftModelfrom transformers import AutoTokenizerimport torchbase_model = AutoModelForCausalLM.from_pretrained( "mistralai/Mistral-7B-Instruct-v0.1")tokenizer = AutoTokenizer.from_pretrained( "mistralai/Mistral-7B-Instruct-v0.1")model = PeftModel.from_pretrained( base_model, "maomao88/anime-waifu-mistral-lora")def chat_with_personality(trait, user_input, max_new_tokens=100, temperature=0.8): """ Generate a response from the fine-tuned model using a given personality trait. """ messages = [ { "role": "system", "content": f"You are an anime character with the following personality: {trait}." }, { "role": "user", "content": user_input } ] # Apply Mistral's chat template prompt = tokenizer.apply_chat_template( messages, tokenize=False, add_generation_prompt=True ) inputs = tokenizer(prompt, return_tensors="pt").to(model.device) with torch.no_grad(): outputs = model.generate( **inputs, max_new_tokens=max_new_tokens, do_sample=True, temperature=temperature, top_p=0.9, pad_token_id=tokenizer.eos_token_id, repetition_penalty=1.1 ) # Decode only the generated text portion (skip <s> etc.) response = tokenizer.decode(outputs[0], skip_special_tokens=True) # Remove the prompt portion to keep only the assistant reply if "[/INST]" in response: response = response.split("[/INST]")[-1].strip() return responsechat_with_personality("tsundere", "What do you think of the moon?")# Response Example: It’s not like I care about the moon or anything… but it sure is pretty tonight!