README.md

metadata

license: other
license_name: license
license_link: https://huggingface.co/Qwen/Qwen1.5-0.5B/blob/main/LICENSE

A fine-tuned version of the Qwen/Qwen1.5-0.5B model, the data set used is alpaca_gpt4_data_zh.json

· Call example ```python

import os

from transformers import AutoModelForCausalLM, AutoTokenizer

messages = [ {"role": "system", "content": "You are a helpful assistant."}, ]

device = "cuda" # the device to load the model onto model_path = os.path.dirname(file) model = AutoModelForCausalLM.from_pretrained( model_path, torch_dtype="auto", device_map="auto" ) tokenizer = AutoTokenizer.from_pretrained(model_path) response = '' if name == 'main':

while True:
    # prompt = "Give me a short introduction to large language model."
    prompt = input("input:")
    messages.append({"role": "user", "content": prompt})
    text = tokenizer.apply_chat_template(
        messages,
        tokenize=False,
        add_generation_prompt=True
    )
    model_inputs = tokenizer([text], return_tensors="pt").to(device)

    generated_ids = model.generate(
        model_inputs.input_ids,
        max_new_tokens=512
    )
    generated_ids = [
        output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
    ]

    response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
    print(response)
    messages.append({"role": "system", "content": response}, )

```