Upload app.py

app.py

@@ -4,7 +4,7 @@ import gradio as gr
 from fastai.vision.all import *
 import skimage
 
-learn = load_learner('fast-ai/OxfordPetAI/export.pkl')
+learn = load_learner('export.pkl')
 
 labels = learn.dls.vocab
 def predict(img):
@@ -14,6 +14,6 @@ def predict(img):
 
 # Create and launch the Gradio interface
 title = "Pet Breed Classifier"
-examples = ['fast-ai/OxfordPetAI/beagle.jpeg']
+examples = ['beagle.jpeg']
 description = "A pet breed classifier trained on the Oxford Pets dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces."
 gr.Interface(fn=predict, inputs="image", outputs="label", title=title, description=description, examples=examples).launch(share=True)