# app.py
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

# 加载模型和分词器
model_name = "deepseek-ai/deepseek-math-7b-instruct"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map="auto")

# 输入数学题
input_text = "解方程 2x + 5 = 15。"

# 生成解答
inputs = tokenizer(input_text, return_tensors="pt").to("cuda")
outputs = model.generate(**inputs, max_length=100)
generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)

# 输出结果
print("问题：", input_text)
print("解答：", generated_text)