Update app.py

app.py

@@ -74,8 +74,8 @@ UI=gr.Interface(fn=image_to_output,
              article="*built by qmjnh*"
              )
 
-description = "This model was trained to recognize 102 types flowers. For the model to work with high-accuracy, refer to the trained flowers [here](https://huggingface.co/spaces/qmjnh/flowerClassification_2/blob/main/flower_names.txt)"
-article1="This is an AI model trained to predict the name of the flower in the input picture, given that the flower is one of 102 types of flowers (flowers list can be found [here](https://huggingface.co/spaces/qmjnh/flowerClassification_2/blob/main/flower_names.txt) ). To try out the model, simply drop/upload a picture into the '*input box*' and press 'Submit'. The predictions will show up in the '*output box*'\n"
+description = "This model was trained to recognize 102 types of flowers. For the model to work with high-accuracy, refer to the trained flowers [here](https://huggingface.co/spaces/qmjnh/flowerClassification_2/blob/main/flower_names.txt)"
+article1="This is an AI model trained to predict the name of the flower in the input picture. To try out the model, simply drop/upload a picture into the '*input box*' and press 'Submit'. The predictions will show up in the '*output box*'\n. Since the model was only trained to classify 102 types of flowers (flowers list can be found [here](https://huggingface.co/spaces/qmjnh/flowerClassification_2/blob/main/flower_names.txt) ), the prediction might be incorrect, but chances are if you try googling the names predicted by the model, the resulting flower will be very familiar to that in your picture. "
 article2="\n *built by qmjnh*"
 UI=gr.Interface(fn=image_to_output, 
              inputs=gradio_image(shape=(224,224)),