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app.py

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+import streamlit as st
+from transformers import pipeline
+import torch
+
+# Load the text-to-text generation pipeline
+pipe = pipeline("text2text-generation", model="samanjoy2/bn2ipa_TwoBraincells", device='cpu')
+
+st.title("Bangla Text to IPA Transcription")
+
+# User input for text generation
+input_text = st.text_area("Enter Bangla text for IPA Transcription:", max_chars=400)
+
+if st.button("Generate IPA"):
+    if input_text:
+        # Generate text using the pipeline
+        generated_text = pipe(input_text, max_length=512, batch_size=1)[0]['generated_text']
+
+        # Display the generated text
+        st.subheader("Generated IPA:")
+        st.write(generated_text)
+    else:
+        st.warning("Please enter text for generation.")

requirements.txt

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+streamlit
+transformers
+torch