thomasm291678
feat: 纳入 DAPT AI 引擎 vetnetv2.0 + 测试报告修复(语言约束/must_not_miss兜底/降温度/sdpa) + KB 走 git-lfs
9a71f08 | """快速测试 DAPT 模型是否正常工作""" | |
| import time, torch, sys, os | |
| model_path = r"C:\Users\HP\Downloads\vet-qwen3b-v3-dapt-model\vet-qwen3b-v3-dapt" | |
| print("=" * 50) | |
| print("DAPT 模型快速测试") | |
| print("=" * 50) | |
| # 加载 | |
| print("\n[1] 加载模型...") | |
| t0 = time.time() | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| model = AutoModelForCausalLM.from_pretrained( | |
| model_path, | |
| torch_dtype=torch.bfloat16, | |
| device_map="auto", | |
| trust_remote_code=True, | |
| low_cpu_mem_usage=True, | |
| ) | |
| tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True) | |
| tokenizer.pad_token = tokenizer.eos_token | |
| print(f"[1] 加载完成 ({time.time()-t0:.1f}s)") | |
| print(f" 设备: {model.device}") | |
| print(f" 显存: {torch.cuda.memory_allocated()/1e9:.1f}GB / {torch.cuda.get_device_properties(0).total_memory/1e9:.1f}GB") | |
| # 简单推理 | |
| print("\n[2] 推理测试...") | |
| prompt = """你是兽医专家。请回答以下问题： | |
| 一只3岁金毛犬连续呕吐2天，呕吐物为黄色胆汁。精神差，不吃东西。体温39.5°C。 | |
| 请问最可能的鉴别诊断是什么？""" | |
| messages = [ | |
| {"role": "system", "content": "你是资深兽医专家。"}, | |
| {"role": "user", "content": prompt}, | |
| ] | |
| text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) | |
| inputs = tokenizer(text, return_tensors="pt").to(model.device) | |
| t0 = time.time() | |
| with torch.no_grad(): | |
| outputs = model.generate(**inputs, max_new_tokens=500, temperature=0.3, do_sample=True, top_p=0.9, pad_token_id=tokenizer.eos_token_id) | |
| elapsed = time.time() - t0 | |
| response = tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True) | |
| print(f"[2] 推理完成 ({elapsed:.1f}s)") | |
| print(f" Token: {inputs.input_ids.shape[1]} → {outputs.shape[1]-inputs.input_ids.shape[1]}") | |
| print(f"\n--- 回复 ---\n{response}\n") | |
| # 清理 | |
| del model, tokenizer | |
| torch.cuda.empty_cache() | |
| print("[3] 清理完成") | |