Upload 2 files

app.py

@@ -0,0 +1,16 @@
+from transformers import BartForSequenceClassification, BartTokenizer
+import gradio as grad
+bart_tkn = BartTokenizer.from_pretrained('facebook/bart-large-mnli')
+mdl = BartForSequenceClassification.from_pretrained('facebook/bart-large-mnli')
+
+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()

requirements.txt

@@ -0,0 +1,4 @@
+gradio
+transformers
+torch
+