Update app.py

app.py

@@ -8,36 +8,39 @@ from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 import torch
 import gdown
 
-# Download the model from Google Drive
-@st.cache(allow_output_mutation=True)
-def load_model_from_gdrive():
-    url = https://drive.google.com/drive/folders/19P3ZcWor8znyaOMJgx_gaHuOyf4alnP3?usp=drive_link  # Replace with your actual Google Drive link
-    output = 'model.zip'
-    gdown.download(url, output, quiet=False)
-    # Unzip the model
-    import zipfile
-    with zipfile.ZipFile(output, 'r') as zip_ref:
-        zip_ref.extractall('model')
-    # Load the model and tokenizer
-    model = AutoModelForSeq2SeqLM.from_pretrained('model')
-    tokenizer = AutoTokenizer.from_pretrained('model')
-    return model, tokenizer
+import streamlit as st
+from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
 
-model, tokenizer = load_model_from_gdrive()
-summarizer = pipeline("summarization", model=model, tokenizer=tokenizer)
+# Load the model and tokenizer
+model_path = '.' 
 
-# Streamlit app
-st.title("Text Summarization App")
-st.write("Enter the text you want to summarize:")
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_path)
+summarizer = pipeline('summarization', model=model, tokenizer=tokenizer)
 
-# Text input
-user_input = st.text_area("Text to summarize", height=200)
+st.title("Text Summarization with Fine-Tuned Model")
+st.write("Enter text to generate a summary using the fine-tuned summarization model.")
 
-# Summarize text
+text = st.text_area("Input Text", height=200)
 if st.button("Summarize"):
-    if user_input:
-        summary = summarizer(user_input, max_length=130, min_length=30, do_sample=False)
-        st.subheader("Summary:")
-        st.write(summary[0]['summary_text'])
+    if text:
+        with st.spinner("Summarizing..."):
+            summary = summarizer(text, max_length=150, min_length=30, do_sample=False)
+            st.success("Summary Generated")
+            st.write(summary[0]['summary_text'])
     else:
-        st.write("Please enter text to summarize.")
+        st.warning("Please enter some text to summarize.")
+
+if __name__ == "__main__":
+    st.set_option('deprecation.showfileUploaderEncoding', False)
+    st.markdown(
+        """
+        <style>
+        .reportview-container {
+            flex-direction: row;
+            justify-content: center;
+        }
+        </style>
+        """,
+        unsafe_allow_html=True
+    )