Create app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+
+
+# Model in Hugging Hub
+tokenizer = AutoTokenizer.from_pretrained("Andresmfs/st5s-es-inclusivo")
+model = AutoModelForSeq2SeqLM.from_pretrained("Andresmfs/st5s-es-inclusivo")
+
+def make_neutral(phrase):
+    # Define prompt for converting gendered text to neutral
+    input_ids = tokenizer(phrase, return_tensors="pt").input_ids
+
+    # Call the LLM to generate neutral text
+    outputs = model.generate(input_ids)
+
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+
+
+    
+iface = gr.Interface(
+    fn=make_neutral,
+    inputs="text",
+    outputs="text",
+    title="ES Inclusive Language",
+    description="Enter a Spanish phrase and get it converted into neutral/inclusive form."
+)
+iface.launch()