Create app.py

app.py

@@ -0,0 +1,16 @@
+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Load the pre-trained model and tokenizer
+model_name = "facebook/opt-1.3b"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Create the Streamlit app
+st.title("Text Summarization App")
+text_input = st.text_input("Enter text to summarize")
+if st.button("Summarize"):
+    input_ids = tokenizer.encode(text_input, return_tensors="pt")
+    summary_ids = model.generate(input_ids, max_length=100, min_length=20, do_sample=False)
+    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+    st.write(summary)