Create app.py

app.py

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+from transformers import BartForSequenceClassification, BartTokenizer
+import gradio as grad
+
+model_name = "facebook/bart-large-mnli"
+bart_tokenizer = BartTokenizer.from_pretrained(model_name)
+model = BartForSequenceClassification.from_pretrained(model_name)
+
+def classify(text, label):
+    token_ids = bart_tokenizer.encode(text, label, return_tensors="pt")
+    token_logits = model(token_ids)[0]
+    entail_contra_token_logits = token_logits[:, [0, 2]]
+    probabilities = entail_contra_token_logits.softmax(dim=1)
+    response = probabilities[:, 1].item() * 100
+    return response
+
+in_text = grad.Textbox(lines=1, label="English", placeholder="Text to be classified")
+in_labels = grad.Textbox(lines=1, label="Label", placeholder="Input a label")
+out = grad.Textbox(lines=1, label="Probability of label being true is ")
+
+grad.Interface(classify, inputs=[in_text, in_labels], outputs=[out]).launch()