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saurabhati
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DASS_medium_AudioSet_50.2

Audio Classification
Transformers
Safetensors
dass
PyTorch
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Mamba
custom_code
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Update README.md

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@@ -21,9 +21,9 @@ import torch
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  import librosa
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  from transformers import AutoConfig, AutoModelForAudioClassification, AutoFeatureExtractor
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- config = AutoConfig.from_pretrained('saurabhati/DASS_small_AudioSet_50.2',trust_remote_code=True)
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- audio_model = AutoModelForAudioClassification.from_pretrained('saurabhati/DASS_small_AudioSet_50.2',trust_remote_code=True)
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- feature_extractor = AutoFeatureExtractor.from_pretrained('saurabhati/DASS_small_AudioSet_50.2',trust_remote_code=True)
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  waveform, sr = librosa.load("audio/eval/_/_/--4gqARaEJE_0.000.flac", sr=16000)
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  inputs = feature_extractor(waveform,sr, return_tensors='pt')
 
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  import librosa
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  from transformers import AutoConfig, AutoModelForAudioClassification, AutoFeatureExtractor
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+ config = AutoConfig.from_pretrained('saurabhati/DASS_medium_AudioSet_50.2',trust_remote_code=True)
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+ audio_model = AutoModelForAudioClassification.from_pretrained('saurabhati/DASS_medium_AudioSet_50.2',trust_remote_code=True)
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+ feature_extractor = AutoFeatureExtractor.from_pretrained('saurabhati/DASS_medium_AudioSet_50.2',trust_remote_code=True)
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  waveform, sr = librosa.load("audio/eval/_/_/--4gqARaEJE_0.000.flac", sr=16000)
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  inputs = feature_extractor(waveform,sr, return_tensors='pt')