143 lines
4.6 KiB
Python
143 lines
4.6 KiB
Python
from pathlib import Path
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from typing import Annotated, Union
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import typer
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from peft import PeftModelForCausalLM
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from transformers import (
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AutoModel,
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AutoTokenizer,
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)
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import torch
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app = typer.Typer(pretty_exceptions_show_locals=False)
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def load_model_and_tokenizer(
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model_dir: Union[str, Path], trust_remote_code: bool = True
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):
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model_dir = Path(model_dir).expanduser().resolve()
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if (model_dir / "adapter_config.json").exists():
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import json
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with open(model_dir / "adapter_config.json", "r", encoding="utf-8") as file:
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config = json.load(file)
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model = AutoModel.from_pretrained(
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config.get("base_model_name_or_path"),
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trust_remote_code=trust_remote_code,
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device_map="auto",
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torch_dtype=torch.bfloat16,
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)
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model = PeftModelForCausalLM.from_pretrained(
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model=model,
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model_id=model_dir,
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trust_remote_code=trust_remote_code,
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)
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tokenizer_dir = model.peft_config["default"].base_model_name_or_path
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else:
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model = AutoModel.from_pretrained(
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model_dir,
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trust_remote_code=trust_remote_code,
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device_map="auto",
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torch_dtype=torch.bfloat16,
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)
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tokenizer_dir = model_dir
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tokenizer = AutoTokenizer.from_pretrained(
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tokenizer_dir,
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trust_remote_code=trust_remote_code,
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encode_special_tokens=True,
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use_fast=False,
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)
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return model, tokenizer
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@app.command()
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def main(
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model_dir: Annotated[str, typer.Argument(help="")],
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):
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# For GLM-4 Finetune Without Tools
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messages = [
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{
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"role": "user",
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"content": "#裙子#夏天",
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}
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]
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# For GLM-4 Finetune With Tools
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# messages = [
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# {
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# "role": "system", "content": "",
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# "tools":
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# [
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# {
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# "type": "function",
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# "function": {
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# "name": "create_calendar_event",
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# "description": "Create a new calendar event",
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# "parameters": {
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# "type": "object",
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# "properties": {
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# "title": {
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# "type": "string",
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# "description": "The title of the event"
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# },
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# "start_time": {
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# "type": "string",
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# "description": "The start time of the event in the format YYYY-MM-DD HH:MM"
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# },
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# "end_time": {
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# "type": "string",
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# "description": "The end time of the event in the format YYYY-MM-DD HH:MM"
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# }
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# },
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# "required": [
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# "title",
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# "start_time",
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# "end_time"
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# ]
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# }
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# }
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# }
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# ]
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#
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# },
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# {
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# "role": "user",
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# "content": "Can you help me create a calendar event for my meeting tomorrow? The title is \"Team Meeting\". It starts at 10:00 AM and ends at 11:00 AM."
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# },
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# ]
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# For GLM-4V Finetune
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# messages = [
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# {
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# "role": "user",
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# "content": "女孩可能希望观众做什么？",
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# "image": Image.open("your Image").convert("RGB")
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# }
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# ]
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model, tokenizer = load_model_and_tokenizer(model_dir)
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inputs = tokenizer.apply_chat_template(
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messages,
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add_generation_prompt=True,
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tokenize=True,
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return_tensors="pt",
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return_dict=True,
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).to(model.device)
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generate_kwargs = {
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"max_new_tokens": 1024,
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"do_sample": True,
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"top_p": 0.8,
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"temperature": 0.8,
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"repetition_penalty": 1.2,
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"eos_token_id": model.config.eos_token_id,
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}
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outputs = model.generate(**inputs, **generate_kwargs)
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response = tokenizer.decode(
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outputs[0][len(inputs["input_ids"][0]) :], skip_special_tokens=True
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).strip()
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print("=========")
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print(response)
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if __name__ == "__main__":
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app()
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