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1from transformers import AutoModelForCausalLM, AutoTokenizer
2from peft import PeftModel
3model_path = "Rakuten/RakutenAI-7B-instruct"
4tokenizer = AutoTokenizer.from_pretrained(model_path)
5model = AutoModelForCausalLM.from_pretrained(model_path, torch_dtype=torch.bfloat16, device_map="auto")
6model = PeftModel.from_pretrained(
7 model,
8 "Kendamarron/math-problem-generator_RakutenAI-7B-instruct_lora"
9)
10model.eval()
11
12theme = "整数の四則演算"
13system_message = """A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: 次の要素を使った算数の文章問題を作成してください。
14要素: {user_input} ASSISTANT: """
15
16inputs = tokenizer(system_message.format(user_input=theme), return_tensors="pt").to(device=model.device)
17
18with torch.no_grad():
19 outputs = model.generate(
20 **inputs,
21 max_new_tokens=256,
22 do_sample=True,
23 temperature=0.8,
24 eos_token_id=tokenizer.eos_token_id
25)
26
27print(tokenizer.decode(outputs[0],skip_special_tokens=True))