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wav2vec2-base-cs-50k

Inference Endpoints

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jlehecka commited on Jul 23

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e06d317

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1 Parent(s): 1a1073b

Update README.md

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@@ -43,7 +43,7 @@ This model can be used e.g. to extract per-frame contextual embeddings from audi
 from transformers import Wav2Vec2Model, Wav2Vec2FeatureExtractor
 import torchaudio
-feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained("fav-kky/wav2vec2-base-cs-80k-ClTRUS")
 model = Wav2Vec2Model.from_pretrained("fav-kky/wav2vec2-base-cs-50k")
 speech_array, sampling_rate = torchaudio.load("/path/to/audio/file.wav")

 from transformers import Wav2Vec2Model, Wav2Vec2FeatureExtractor
 import torchaudio
+feature_extractor = Wav2Vec2FeatureExtractor.from_pretrained("fav-kky/wav2vec2-base-cs-50k")
 model = Wav2Vec2Model.from_pretrained("fav-kky/wav2vec2-base-cs-50k")
 speech_array, sampling_rate = torchaudio.load("/path/to/audio/file.wav")