1!pip install bitsandbytes accelerate
2!pip install transformers torch
1from transformers import AutoTokenizer, AutoModelForCausalLM
2import torch
3
4# 加载模型和tokenizer
5tokenizer = AutoTokenizer.from_pretrained("bysq/autism-assistant-qwen2")
6model = AutoModelForCausalLM.from_pretrained("bysq/autism-assistant-qwen2")
7
8# 移动到GPU（如果可用）
9device = "cuda" if torch.cuda.is_available() else "cpu"
10model = model.to(device)
11
12# 使用示例
13def analyze_expression(original_text, autism_expression):
14 prompt = f'''你是一个专门帮助理解自闭症患者表达的AI助手。
15原始表达："{original_text}"
16自闭症患者的表达："{autism_expression}"
17
18请分析并回答：
19- 情感分析：'''
20
21 inputs = tokenizer(prompt, return_tensors="pt").to(device)
22
23 with torch.no_grad():
24 outputs = model.generate(
25 **inputs,
26 max_new_tokens=200,
27 do_sample=True,
28 temperature=0.7,
29 pad_token_id=tokenizer.pad_token_id
30 )
31
32 response = tokenizer.decode(outputs[0], skip_special_tokens=True)
33 return response[len(prompt):].strip()
34
35# 测试
36result = analyze_expression("可以把东西给我？", "不你")
37print(result)
