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app.py

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+
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import torch
+
+MODEL_NAME = "millan24/opus-books-en-fr-finetuned"
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_NAME)
+model.eval()
+
+def translate(text):
+    inputs = tokenizer(text, return_tensors="pt", truncation=True, max_length=128)
+    with torch.no_grad():
+        outputs = model.generate(**inputs, max_length=128)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+demo = gr.Interface(
+    fn=translate,
+    inputs=gr.Textbox(lines=4, placeholder="Enter English text here..."),
+    outputs=gr.Textbox(lines=4, label="French translation"),
+    title="English → French Translator",
+    description="Fine-tuned model on opus_books dataset (en-fr)",
+    examples=[
+        ["The sun was setting over the mountains."],
+        ["She opened the door and stepped into the room."],
+        ["It was a cold and rainy night in Paris."],
+    ]
+)
+
+demo.launch()