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FAVA, a verification model.
```
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 = "Read the following references:\n{evidence}\nPlease identify all the errors in the following text using the information in the references provided and suggest edits if necessary:\n[Text] {output}\n[Edited] "
output = "" # add your passage to verify
evidence = "" # add a piece of evidence
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])
``` |