Uploading our food not food classifier demo from a notebook!

app.py

@@ -9,8 +9,16 @@ from transformers import pipeline
 food_not_food_classifier = pipeline(task="text-classification",
                                     model="tonicanada/learn_hf_food_not_food_text_classifier-distilbert-base-uncased",
                                     top_k=1,
+                                    device="cuda" if torch.cuda.is_available() else "cpu",
                                     batch_size=32)
 
+def classify_text(text):
+    # Usa el clasificador
+    result = food_not_food_classifier(text)
+    # Devuelve la etiqueta y la puntuación
+    return result[0]['label'], result[0]['score']
+    
+
 # 3. Create a Gradio interface
 description = """
 A text classifier to determine if a sentence is about food or not food. 
@@ -21,9 +29,9 @@ See [source code](https://github.com/mrdbourke/learn-huggingface/blob/main/noteb
 """
 
 demo = gr.Interface(
-    fn = food_not_food_classifier,
+    fn = classify_text,
     inputs = "text",
-    outputs=gr.Label(num_top_classes=2),
+    outputs=[gr.Label(num_top_classes=2), gr.Textbox()],
     title="🍗🚫🥑 Food or Not Food Text Classifier",
     description=description,
     examples=[["I whipped up a fresh batch of code, but it seems to have a syntax error."],