Update README.md

README.md

@@ -2,9 +2,19 @@ FAVA, a verification model.
 
 ```
 import torch
+import vllm
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 
-tokenizer = AutoTokenizer.from_pretrained("abhika-m/FAVA")
-fava = AutoModelForSequenceClassification.from_pretrained("abhika-m/FAVA")
-
+model = vllm.LLM(model="fava-uw/fava-model")
+sampling_params = vllm.SamplingParams(
+  temperature=0,
+  top_p=1.0,
+  max_tokens=1024,
+)
+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])
 ```