Create app.py

app.py

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+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+import gradio as gr
+
+MODEL_ID = "adcelis/opus-books-en-es-flan-t5-small"
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
+model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_ID)
+
+def translate_text(text):
+    if not text or not text.strip():
+        return ""
+
+    prompt = f"translate English to Spanish: {text}"
+
+    inputs = tokenizer(prompt, return_tensors="pt", truncation=True)
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=128
+    )
+
+    result = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return result
+
+demo = gr.Interface(
+    fn=translate_text,
+    inputs=gr.Textbox(
+        lines=5,
+        label="Texto en inglés",
+        placeholder="Write here the English sentence you want to translate..."
+    ),
+    outputs=gr.Textbox(
+        lines=5,
+        label="Traducción al español"
+    ),
+    title="English to Spanish Translation",
+    description="Demo del modelo fine-tuned con opus_books para traducir texto del inglés al español.",
+    examples=[
+        ["The house was quiet and the children were sleeping."],
+        ["I have never seen such a beautiful garden."],
+        ["She opened the window and looked at the sea."]
+    ],
+    allow_flagging="never"
+)
+
+if __name__ == "__main__":
+    demo.launch()