Delete app.py

app.py

@@ -1,24 +0,0 @@
-from fastai.text.all import *
-import gradio as gr
-from huggingface_hub import from_pretrained_fastai
-
-# Cargamos el learner
-repo_id = "ikerml/twitter_class"
-
-learner = from_pretrained_fastai(repo_id)
-
-# Definimos las etiquetas de nuestro modelo
-labels = ['❤','😍','😂','💕','🔥','😊','😎','✨','💙','😘','📷','🇺🇸','☀','💜','😉','💯','😁','🎄','📸','😜']
-
-example1 = "I like potatoe"
-example2 = "My house is on fire"
-example3 = "The other day, i eat a banana"
-
-# Definimos una función que se encarga de llevar a cabo las predicciones
-def predict(text):
-    pred= learner.predict(text)
-    probs = pred['probs']
-    return {labels[i]: float(probs[i]) for i in range(len(labels))}
-    
-# Creamos la interfaz y la lanzamos. 
-gr.Interface(fn=predict, inputs=gr.inputs.Textbox(), outputs=gr.outputs.Label(),examples=[example1,example2,example3]).launch(share=False)