Create app.py

app.py

@@ -0,0 +1,16 @@
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+import gradio as grad
+tokenizer = AutoTokenizer.from_pretrained("oigele/Fb_improved_zeroshot")
+model = AutoModelForSequenceClassification.from_pretrained("oigele/Fb_improved_zeroshot")
+
+def classify(text,label): 
+    tkn_ids = bart_tkn.encode(text, label, return_tensors='pt')
+    tkn_lgts = mdl(tkn_ids)[0]
+    entail_contra_tkn_lgts = tkn_lgts[:,[0,2]]
+    probab = entail_contra_tkn_lgts.softmax(dim=1)
+    response =  probab[:,1].item() * 100 
+    return response
+txt=grad.Textbox(lines=1, label="English", placeholder="text to be classified")
+labels=grad.Textbox(lines=1, label="Label", placeholder="Input a Label")
+out=grad.Textbox(lines=1, label="Probablity of label being true is")
+grad.Interface(classify, inputs=[txt,labels], outputs=out).launch()