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--- |
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datasets: |
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- IlyaGusev/gpt_roleplay_realm |
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language: |
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- en |
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pipeline_tag: text-generation |
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--- |
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|
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LLaMA 7B fine-tuned on the English part of the `gpt_roleplay_realm` dataset. |
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Code example: |
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``` |
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from peft import PeftModel, PeftConfig |
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from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig |
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MODEL_NAME = "IlyaGusev/rpr_7b" |
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DEFAULT_MESSAGE_TEMPLATE = "<s>{role}\n{content}</s>\n" |
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class Conversation: |
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def __init__( |
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self, |
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system_prompt, |
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message_template=DEFAULT_MESSAGE_TEMPLATE, |
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start_token_id=1, |
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bot_token_id=9225 |
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): |
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self.message_template = message_template |
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self.start_token_id = start_token_id |
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self.bot_token_id = bot_token_id |
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self.messages = [{ |
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"role": "system", |
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"content": system_prompt |
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}] |
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def get_start_token_id(self): |
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return self.start_token_id |
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def get_bot_token_id(self): |
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return self.bot_token_id |
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def add_user_message(self, message): |
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self.messages.append({ |
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"role": "user", |
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"content": message |
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}) |
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def add_bot_message(self, message): |
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self.messages.append({ |
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"role": "bot", |
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"content": message |
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}) |
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def get_prompt(self, tokenizer): |
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final_text = "" |
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for message in self.messages: |
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message_text = self.message_template.format(**message) |
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final_text += message_text |
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final_text += tokenizer.decode([self.start_token_id, self.bot_token_id]) |
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return final_text.strip() |
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def generate(model, tokenizer, prompt, generation_config): |
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data = tokenizer(prompt, return_tensors="pt") |
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data = {k: v.to(model.device) for k, v in data.items()} |
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output_ids = model.generate(**data,generation_config=generation_config)[0] |
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output_ids = output_ids[len(data["input_ids"][0]):] |
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output = tokenizer.decode(output_ids, skip_special_tokens=True) |
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return output.strip() |
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config = PeftConfig.from_pretrained(MODEL_NAME) |
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model = AutoModelForCausalLM.from_pretrained( |
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config.base_model_name_or_path, |
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load_in_8bit=True, |
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torch_dtype=torch.float16, |
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device_map="auto" |
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) |
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model = PeftModel.from_pretrained( |
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model, |
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MODEL_NAME, |
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torch_dtype=torch.float16 |
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) |
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model.eval() |
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tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME) |
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generation_config = GenerationConfig.from_pretrained(MODEL_NAME) |
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print(generation_config) |
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system_prompt = "You are Chiharu Yamada. Chiharu Yamada is a young, computer engineer-nerd with a knack for problem solving and a passion for technology." |
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conversation = Conversation(system_prompt=system_prompt) |
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for inp in inputs: |
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inp = input() |
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conversation.add_user_message(inp) |
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prompt = conversation.get_prompt(tokenizer) |
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output = generate(model, tokenizer, prompt, generation_config) |
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conversation.add_bot_message(output) |
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print(output) |
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``` |
