Create app.py

app.py

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+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+# Load your trained model and tokenizer from Hugging Face
+model_name = "ENGLISH TO TELUGU"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+# Streamlit UI
+st.title("Colloquial Language Translator")
+st.write("Enter English text to translate into the colloquial language of your choice.")
+
+# User input
+input_text = st.text_input("Enter English text:")
+
+# When the button is clicked
+if st.button("Translate"):
+    if input_text:
+        # Tokenize and generate output
+        inputs = tokenizer(input_text, return_tensors="pt", padding=True, truncation=True)
+        outputs = model.generate(**inputs)
+        translation = tokenizer.decode(outputs[0], skip_special_tokens=True)
+        
+        # Display the result
+        st.success(f"Translation: {translation}")
+    else:
+        st.warning("Please enter some text to translate.")