Update app.py

app.py

@@ -9,10 +9,15 @@ import numpy as np
 # Set device
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
-# Load the fine-tuned model and processor
-model = Wav2Vec2ForSequenceClassification.from_pretrained("./fine_tuned_model", use_safetensors=True).to(device)
+# Load the processor
 processor = Wav2Vec2Processor.from_pretrained("./fine_tuned_model")
 
+# Load the model
+model = Wav2Vec2ForSequenceClassification.from_pretrained("facebook/wav2vec2-base-960h", num_labels=len(pd.read_csv("dataset/train_wav.csv")["Common Name"].unique()))
+model.load_state_dict(torch.load("./fine_tuned_model/model.pt", map_location=device))
+model.to(device)
+model.eval()
+
 # Load the label encoder
 label_encoder = LabelEncoder()
 label_encoder.fit(pd.read_csv("dataset/train_wav.csv")["Common Name"])