Update README.md

README.md

@@ -1,3 +1,99 @@
 ---
 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 : 18810979033@163.com
+# @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()
+```