Create app.py

app.py

@@ -0,0 +1,27 @@
+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+# Load the Hugging Face model
+@st.cache_resource
+def load_model():
+    tokenizer = AutoTokenizer.from_pretrained("t5-small")  # Change model if needed
+    model = AutoModelForSeq2SeqLM.from_pretrained("t5-small")
+    return tokenizer, model
+
+tokenizer, model = load_model()
+
+# App UI
+st.title("Paraphrasing Tool - AI to Human")
+st.write("Paste your AI-generated text below to humanize it:")
+
+input_text = st.text_area("Enter text here:")
+if st.button("Paraphrase"):
+    if input_text.strip():
+        with st.spinner("Paraphrasing..."):
+            inputs = tokenizer.encode("paraphrase: " + input_text, return_tensors="pt", max_length=512, truncation=True)
+            outputs = model.generate(inputs, max_length=512, num_beams=4, early_stopping=True)
+            paraphrased_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+        st.success("Here is the paraphrased text:")
+        st.write(paraphrased_text)
+    else:
+        st.error("Please enter some text to paraphrase.")