ok

api.py

@@ -31,6 +31,7 @@ def download_models(specific_models=None):
     """
     MODELS = {
         'autoregressive.pth': 'https://huggingface.co/jbetker/tortoise-tts-v2/resolve/hf/.models/autoregressive.pth',
+        'classifier.pth': 'https://huggingface.co/jbetker/tortoise-tts-v2/resolve/hf/.models/classifier.pth',
         'clvp.pth': 'https://huggingface.co/jbetker/tortoise-tts-v2/resolve/hf/.models/clvp.pth',
         'cvvp.pth': 'https://huggingface.co/jbetker/tortoise-tts-v2/resolve/hf/.models/cvvp.pth',
         'diffusion_decoder.pth': 'https://huggingface.co/jbetker/tortoise-tts-v2/resolve/hf/.models/diffusion_decoder.pth',
@@ -153,7 +154,7 @@ def classify_audio_clip(clip):
     :param clip: torch tensor containing audio waveform data (get it from load_audio)
     :return: True if the clip was classified as coming from Tortoise and false if it was classified as real.
     """
-    download_models(['classifier'])
+    download_models(['classifier.pth'])
     classifier = AudioMiniEncoderWithClassifierHead(2, spec_dim=1, embedding_dim=512, depth=5, downsample_factor=4,
                                                     resnet_blocks=2, attn_blocks=4, num_attn_heads=4, base_channels=32,
                                                     dropout=0, kernel_size=5, distribute_zero_label=False)

results/.gitattributes

@@ -0,0 +1,5 @@
+favorite_riding_hood.mp3 filter=lfs diff=lfs merge=lfs -text
+favorites filter=lfs diff=lfs merge=lfs -text
+riding_hood filter=lfs diff=lfs merge=lfs -text
+tacotron_comparison filter=lfs diff=lfs merge=lfs -text
+various filter=lfs diff=lfs merge=lfs -text