Use model pushed to hf-hub

app.py

@@ -8,6 +8,7 @@ import io
 import fastai.vision.all as fai_vision
 import gradio as gr
 import numpy as np
+from huggingface_hub import from_pretrained_fastai
 from PIL import Image
 
 from create_spectrograms import (
@@ -19,7 +20,7 @@ from create_spectrograms import (
 )
 
 
-MODEL = fai_vision.load_learner('fish-sounds-resnet101-balanced-samples-n50')
+MODEL = from_pretrained_fastai('axds/classify-fish-sounds')
 LABELS = {
     0: 'No call',
     1: 'Black grouper call 1',
@@ -74,6 +75,7 @@ iface = gr.Interface(
         gr.outputs.Image(),
         gr.outputs.Label(num_top_classes=3),
     ],
-    examples=["sample-0002.wav", "sample-20088.wav", "sample-2990.wav"]
+    examples=["sample-0002.wav", "sample-20088.wav", "sample-2990.wav"],
+    title="Classify fish sounds from audio files"
 )
 iface.launch()

fish-sounds-resnet101-balanced-samples-n50

@@ -1 +0,0 @@
-../../models/fish-sounds-resnet101-balanced-samples-n50