Create app.py

app.py

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+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
+
+# Load the fine-tuned model and tokenizer
+model_name = "ibrahimgiki/qa_facebook_bart_base"  
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+# Define a custom question-answering pipeline
+qa_pipeline = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
+
+# Streamlit app layout
+st.title("Question Answering with BART")
+
+# Text area for the user to input a question
+question = st.text_area("Enter your question:")
+
+# Submit button
+if st.button("Submit"):
+    if question:
+        # Perform inference using the pipeline
+        result = qa_pipeline(question)
+        answer = result[0]['generated_text']
+        
+        # Display the answer
+        st.write("**Answer:**", answer)
+    else:
+        st.write("Please enter a question.")