Upload app.py

app.py

@@ -20,8 +20,8 @@ def load_pickle(file_path: str, mode: str = "rb", encoding=""):
         return pickle.load(f, encoding=encoding)
 
 # %%
-label2id = load_pickle('/data/audio-classification-pytorch/wav2vec2/results/best/label2id.pkl')
-id2label = load_pickle('/data/audio-classification-pytorch/wav2vec2/results/best/id2label.pkl')
+label2id = load_pickle('label2id.pkl')
+id2label = load_pickle('id2label.pkl')
 
 # %%
 model = AutoModelForAudioClassification.from_pretrained(
@@ -32,7 +32,7 @@ model = AutoModelForAudioClassification.from_pretrained(
 feature_extractor = AutoFeatureExtractor.from_pretrained("facebook/wav2vec2-base")
 
 # %%
-checkpoint = torch.load('/data/audio-classification-pytorch/wav2vec2/results/best/pytorch_model.bin')
+checkpoint = torch.load('pytorch_model.bin')
 
 # %%
 model.load_state_dict(checkpoint)
@@ -52,7 +52,6 @@ def predict(input):
     label_name = id2label[str(label_id)]
 
     return label_name
-
 # %%
 demo = gr.Interface(
     fn=predict,