Create app.py

app.py

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+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForSequenceClassification
+
+# Load TinyBERT
+model_name = "huawei-noah/TinyBERT_General_6L_768D"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+# Streamlit App Title
+st.title("TinyBERT Text Summarization")
+
+# Input text box
+input_text = st.text_area("Enter text for summarization:", height=200)
+
+# Button to perform summarization
+if st.button("Summarize"):
+    if input_text:
+        # Tokenize input text
+        inputs = tokenizer(input_text, return_tensors="pt", truncation=True, padding=True)
+
+        # Get model outputs
+        outputs = model(**inputs)
+
+        # Display output (this is placeholder logic, adjust to your specific task)
+        st.write(f"Model output: {outputs}")
+    else:
+        st.warning("Please enter some text to summarize.")