Update app.py

app.py

@@ -26,9 +26,10 @@ def food_not_food_classifier(text: str) -> Dict[str, float]:
 
 # 3. Create a Gradio interface with details about our app
 description = """
-A text classifier to determine if a sentence is about food or not food.
+A text classifier to determine if the text is about food or not food.
+The original dataset is extended with 20 rows of short phrases for "food" (like "apple"), and "not food" (like "computer")
 
-Fine-tuned from [DistilBERT](https://huggingface.co/distilbert/distilbert-base-uncased) on a [small dataset of food and not food text](https://huggingface.co/datasets/mrdbourke/learn_hf_food_not_food_image_captions).
+Fine-tuned from [DistilBERT](https://huggingface.co/distilbert/distilbert-base-uncased) on a [small dataset of food and not food text](https://huggingface.co/datasets/shlomoc/learn_hf_food_not_food_image_captions).
 
 See [source code](https://github.com/mrdbourke/learn-huggingface/blob/main/notebooks/hugging_face_text_classification_tutorial.ipynb).
 """
@@ -39,7 +40,8 @@ demo = gr.Interface(fn=food_not_food_classifier,
              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."],
-                       ["A delicious photo of a plate of scrambled eggs, bacon and toast."]])
+                       ["A delicious photo of a plate of scrambled eggs, bacon and toast."],
+                       ["apple"]])
 
 # 4. Launch the interface
 if __name__ == "__main__":