v1 trained model

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 from fastai.vision.all import *
 import skimage
 
-learn = load_learner('export.pkl')
+learn = load_learner('model.pkl')
 
 labels = learn.dls.vocab
 def predict(img):
@@ -10,10 +10,9 @@ def predict(img):
     pred,pred_idx,probs = learn.predict(img)
     return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
-title = "Pet Breed Classifier"
-description = "A pet breed classifier trained on the Oxford Pets dataset with fastai. Created as a demo for Gradio and HuggingFace Spaces."
-article="<p style='text-align: center'><a href='https://tmabraham.github.io/blog/gradio_hf_spaces_tutorial' target='_blank'>Blog post</a></p>"
-examples = ['siamese.jpg']
+title = "Food Classifier"
+description = "A food classifier trained on the food 101 dataset with fastai."
+examples = ['hamburger.jpg']
 interpretation='default'
 enable_queue=True
 

model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0307617e16151f4660b3043eb09a8f99605ae3d02bfc193548521589f2d6f229
+size 116673267