Update for latest gradio, instantiate model once

app.py

@@ -1,21 +1,20 @@
 import gradio as gr
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 
+model_name = 'hackathon-pln-es/t5-small-finetuned-spanish-to-quechua'
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
 def translate(text):
-  model_name = 'hackathon-pln-es/t5-small-finetuned-spanish-to-quechua'
-  model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
-  tokenizer = AutoTokenizer.from_pretrained(model_name)
-  
   input = tokenizer(text, return_tensors="pt")
   output = model.generate(input["input_ids"], max_length=40, num_beams=4, early_stopping=True)
-  
   return tokenizer.decode(output[0], skip_special_tokens=True)
   
 title = "Spanish to Quechua translation 🦙"
-inputs = gr.inputs.Textbox(lines=1, label="Text in Spanish")
-outputs = [gr.outputs.Textbox(label="Translated text in Quechua")]
+inputs = gr.Textbox(lines=1, label="Text in Spanish")
+outputs = [gr.Textbox(label="Translated text in Quechua")]
 
-description = "Here use the [t5-small-finetuned-spanish-to-quechua-model](https://huggingface.co/hackathon-pln-es/t5-small-finetuned-spanish-to-quechua) that was trained with [spanish-to-quechua dataset](https://huggingface.co/datasets/hackathon-pln-es/spanish-to-quechua)."
+description = "Here we use the [t5-small-finetuned-spanish-to-quechua-model](https://huggingface.co/hackathon-pln-es/t5-small-finetuned-spanish-to-quechua) that was trained with [spanish-to-quechua dataset](https://huggingface.co/datasets/hackathon-pln-es/spanish-to-quechua)."
 
 article = '''
 ## Challenges
@@ -35,4 +34,4 @@ examples=[
 ]
 
 iface = gr.Interface(fn=translate, inputs=inputs, outputs=outputs, theme="grass", css="styles.css", examples=examples, title=title, description=description, article=article)
-iface.launch(enable_queue=True)
+iface.queue().launch()