second commit

app.py

@@ -1,7 +1,26 @@
 import gradio as gr
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Load your Hugging Face model and tokenizer
+model_name = "dreyyyy/EN-ES"  # Replace with your model ID
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+# Define the prediction function
+def translate_text(input_text):
+    inputs = tokenizer(input_text, return_tensors="pt")
+    outputs = model.generate(**inputs)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=translate_text,
+    inputs="text",
+    outputs="text",
+    title="Text Translation",
+    description="Translate input text using a Hugging Face model."
+)
+
+# Launch the Gradio app
+if __name__ == "__main__":
+    iface.launch()