|
--- |
|
license: llama2 |
|
--- |
|
## 基于Llama2_7B的藏文心理健康支持对话大模型(Tibetan_Mental_Chat) |
|
|
|
## 多轮对话测试demo |
|
```python |
|
# -- coding: utf-8 -- |
|
# @time : |
|
# @author : shajiu |
|
# @email : [email protected] |
|
# @file : .py |
|
# @software: pycharm |
|
from transformers import AutoTokenizer |
|
import torch |
|
|
|
import sys |
|
sys.path.append("../../") |
|
from component.utils import ModelUtils |
|
|
|
|
|
def main(): |
|
# 使用合并后的模型进行推理 |
|
model_name_or_path = 'baichuan-7b-qlora-sft-merge' |
|
adapter_name_or_path = None |
|
|
|
# 使用base model和adapter进行推理 |
|
# model_name_or_path = 'baichuan-inc/Baichuan-7B' |
|
# adapter_name_or_path = 'YeungNLP/firefly-baichuan-7b-qlora-sft' |
|
|
|
# 是否使用4bit进行推理，能够节省很多显存，但效果可能会有一定的下降 |
|
load_in_4bit = False |
|
device = 'cuda' |
|
|
|
# 生成超参配置 |
|
max_new_tokens = 500 # 每轮对话最多生成多少个token |
|
history_max_len = 1000 # 模型记忆的最大token长度 |
|
top_p = 0.9 |
|
temperature = 0.35 |
|
repetition_penalty = 1.0 |
|
|
|
# 加载模型 |
|
model = ModelUtils.load_model( |
|
model_name_or_path, |
|
load_in_4bit=load_in_4bit, |
|
adapter_name_or_path=adapter_name_or_path |
|
).eval() |
|
# 加载tokenizer |
|
tokenizer = AutoTokenizer.from_pretrained( |
|
model_name_or_path, |
|
trust_remote_code=True, |
|
# llama不支持fast |
|
use_fast=False if model.config.model_type == 'llama' else True |
|
) |
|
# QWenTokenizer比较特殊，pad_token_id、bos_token_id、eos_token_id均为None。eod_id对应的token为<|endoftext|> |
|
if tokenizer.__class__.__name__ == 'QWenTokenizer': |
|
tokenizer.pad_token_id = tokenizer.eod_id |
|
tokenizer.bos_token_id = tokenizer.eod_id |
|
tokenizer.eos_token_id = tokenizer.eod_id |
|
|
|
# 记录所有历史记录 |
|
if model.config.model_type != 'chatglm': |
|
history_token_ids = torch.tensor([[tokenizer.bos_token_id]], dtype=torch.long) |
|
else: |
|
history_token_ids = torch.tensor([[]], dtype=torch.long) |
|
|
|
# 开始对话 |
|
utterance_id = 0 # 记录当前是第几轮对话，为了契合chatglm的数据组织格式 |
|
user_input = input('User：') |
|
while True: |
|
utterance_id += 1 |
|
# chatglm使用官方的数据组织格式 |
|
if model.config.model_type == 'chatglm': |
|
user_input = '[Round {}]\n\n问：{}\n\n答：'.format(utterance_id, user_input) |
|
user_input_ids = tokenizer(user_input, return_tensors="pt", add_special_tokens=False).input_ids |
|
# firefly的数据组织格式 |
|
# 为了兼容qwen-7b，因为其对eos_token进行tokenize，无法得到对应的eos_token_id |
|
else: |
|
input_ids = tokenizer(user_input, return_tensors="pt", add_special_tokens=False).input_ids |
|
eos_token_id = torch.tensor([[tokenizer.eos_token_id]], dtype=torch.long) |
|
user_input_ids = torch.concat([input_ids, eos_token_id], dim=1) |
|
history_token_ids = torch.concat((history_token_ids, user_input_ids), dim=1) |
|
model_input_ids = history_token_ids[:, -history_max_len:].to(device) |
|
with torch.no_grad(): |
|
outputs = model.generate( |
|
input_ids=model_input_ids, max_new_tokens=max_new_tokens, do_sample=True, top_p=top_p, |
|
temperature=temperature, repetition_penalty=repetition_penalty, eos_token_id=tokenizer.eos_token_id |
|
) |
|
model_input_ids_len = model_input_ids.size(1) |
|
response_ids = outputs[:, model_input_ids_len:] |
|
history_token_ids = torch.concat((history_token_ids, response_ids.cpu()), dim=1) |
|
response = tokenizer.batch_decode(response_ids) |
|
print("Firefly：" + response[0].strip().replace(tokenizer.eos_token, "")) |
|
user_input = input('User：') |
|
|
|
|
|
if __name__ == '__main__': |
|
main() |
|
``` |
