Create app.py

app.py

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+import streamlit as st
+import ctranslate2
+from transformers import MarianTokenizer
+
+# Load tokenizer and model
+tokenizer = MarianTokenizer.from_pretrained("Helsinki-NLP/opus-mt-tr-ar")  # Use the original tokenizer path
+translator = ctranslate2.Translator("ctranslate")
+
+st.title("Helsinki-NLP/opus-mt-finetune-tr-ota")
+
+input_text = st.text_area("Enter text to translate:")
+
+if st.button("Translate"):
+    # Tokenize input
+    tokens = tokenizer.convert_ids_to_tokens(tokenizer.encode(input_text, return_tensors="pt")[0])
+    # Translate
+    results = translator.translate_batch([tokens], beam_size=5)
+    # Detokenize output
+    output_tokens = results[0].hypotheses[0]
+    translation = tokenizer.decode(tokenizer.convert_tokens_to_ids(output_tokens), skip_special_tokens=True)
+    st.success(translation)