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app.py

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+import gradio as gr
+from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
+
+model_name = "deepset/roberta-base-squad2"
+model = AutoModelForQuestionAnswering.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+def pred(que,cont):
+    nlp = pipeline('question-answering', model=model_name, tokenizer=model_name)
+    QA_input = {
+        'question': que,
+        'context': cont
+    }
+    res = nlp(QA_input)
+    print(res)
+    values = list(res.values())[3]
+
+    return values
+
+
+interface = gr.Interface(fn=pred,
+                         inputs=["text", "text"],
+                         outputs="text",
+                         title='Bullet Point')
+
+interface.launch(inline=False)
+
+

requirements.txt

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+transformers
+gradio
+torch