Create app.py

app.py

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+import gradio as gr
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+import torch
+
+# Cargar el modelo
+model_name = "CeciGonSer/translation_espa_pure_biblia_bart-large-cnn"  # Reemplaza esto por tu modelo en Hugging Face
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+def translate(text):
+    inputs = tokenizer(text, return_tensors="pt", padding=True)
+    with torch.no_grad():
+        translated = model.generate(**inputs)
+    translation = tokenizer.decode(translated[0], skip_special_tokens=True)
+    return translation
+
+# Interfaz Gradio
+interface = gr.Interface(
+    fn=translate,
+    inputs=gr.Textbox(label="Introduce texto en purépecha"),
+    outputs=gr.Textbox(label="Traducción al español")
+)
+
+interface.launch()