Create app.py

app.py

@@ -0,0 +1,25 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load the question answering model
+qa = pipeline("question-answering")
+
+# Define the function to generate the answer
+def generate_answer(context, question):
+    result = qa(question=question, context=context)
+    return result["answer"]
+
+# Define the Gradio interface
+inputs = [
+    gr.inputs.Textbox(label="Enter some context"),
+    gr.inputs.Textbox(label="Enter a question")
+]
+outputs = gr.outputs.Textbox(label="Answer")
+
+title = "Question Answering with Hugging Face"
+description = "Answer questions based on a given context using Hugging Face's question answering model"
+
+iface = gr.Interface(fn=generate_answer, inputs=inputs, outputs=outputs, title=title, description=description)
+
+# Launch the Gradio app
+iface.launch()