test_before.py

from unsloth import FastLanguageModel
from transformers import TextStreamer

# 微调前测试
max_seq_length = 1024
dtype = None
load_in_4bit = True
model, tokenizer = FastLanguageModel.from_pretrained(
    model_name="unsloth/llama-3-8b",
    max_seq_length=max_seq_length,
    dtype=dtype,
    load_in_4bit=load_in_4bit,
)
alpaca_prompt = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.

### Instruction:
{}
### Input:
{}
### Response:
{}"""

FastLanguageModel.for_inference(model)
inputs = tokenizer(
    [
        alpaca_prompt.format(
            "请用中文回答",  # instruction
            "我们如何在日常生活中减少用水？",  # input
            "",  # output
        )
    ], return_tensors="pt").to("cuda")

text_streamer = TextStreamer(tokenizer)
_ = model.generate(**inputs, streamer=text_streamer, max_new_tokens=128)