许可证: MIT

FAVA，一个验证模型。

import torch
import vllm
from transformers import AutoTokenizer, AutoModelForSequenceClassification

model = vllm.LLM(model="fava-uw/fava-model")
sampling_params = vllm.SamplingParams(
  temperature=0,
  top_p=1.0,
  max_tokens=1024,
)

INPUT = "请阅读以下参考资料：\n{evidence}\n请根据提供的参考资料识别以下文本中的所有错误，并在必要时提出修改建议：\n[原文] {output}\n[修改后] "

output = "" # 添加待验证的文本段落
evidence = "" # 添加参考资料
prompts = [INPUT.format_map({"evidence": evidence, "output": output})]
outputs = model.generate(prompts, sampling_params)
outputs = [it.outputs[0].text for it in outputs]
print(outputs[0])