Views
No views yet
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/jimba-instruction-evolver-alpha_RakutenAI-7B-instruct_lora"
9)
10model.eval()
11input_instruction = "今日の夜ご飯を考えてください。"
12system_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: 次の指示文をより複雑なものに修正してください。
13指示文: {orininal_instruction} ASSISTANT: """
14inputs = tokenizer(system_message.format(original_instruction=input_instruction), return_tensors="pt").to(device=model.device)
15with torch.no_grad():
16 outputs = model.generate(
17 **inputs,
18 max_new_tokens=256,
19 do_sample=True,
20 temperature=0.8,
21 eos_token_id=tokenizer.eos_token_id
22)
23print(tokenizer.decode(outputs[0],skip_special_tokens=True))