updated zeroshot

zeroshot_clf.py

@@ -8,7 +8,7 @@ import plotly.express as px
 model=AutoModelForSequenceClassification.from_pretrained('zero_shot_clf/')
 tokenizer=AutoTokenizer.from_pretrained('zero_shot_clf/')
 
-def zero_shot_classification(premise:str,labels:str,model=model,tokenizer=tokenizer):
+def zero_shot_classification(premise: str, labels: str, model= model, tokenizer= tokenizer):
     try:
         labels=labels.split(',')
         labels=[l.lower() for l in labels]
@@ -27,7 +27,7 @@ def zero_shot_classification(premise:str,labels:str,model=model,tokenizer=tokeni
                              return_tensors='pt',
                                  truncation_strategy='only_first')
         output = model(input)
-        entail_contra_prob = output['logits'][:,[0,2]].softmax(dim=1)[:,1].item()
+        entail_contra_prob = output['logits'][:,[0,2]].softmax(dim=1)[:,1].item() #only normalizing entail & contradict probabilties
         labels_prob.append(entail_contra_prob)
 
     labels_prob_norm=[np.round(100*c/np.sum(labels_prob),1) for c in labels_prob]