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wav2vec2-large-960h

Automatic Speech Recognition Transformers PyTorch

English wav2vec2 speech Inference Endpoints

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patrickvonplaten commited on Feb 11, 2021

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@@ -76,7 +76,7 @@ from jiwer import wer
 librispeech_eval = load_dataset("librispeech_asr", "clean", split="test")
 model = Wav2Vec2ForCTC.from_pretrained("facebook/wav2vec2-large-960h").to("cuda")
-tokenizer = Wav2Vec2Tokenizer.from_pretrained("facebook/wav2vec2-base-960h")
 def map_to_array(batch):
     speech, _ = sf.read(batch["file"])

 librispeech_eval = load_dataset("librispeech_asr", "clean", split="test")
 model = Wav2Vec2ForCTC.from_pretrained("facebook/wav2vec2-large-960h").to("cuda")
+tokenizer = Wav2Vec2Tokenizer.from_pretrained("facebook/wav2vec2-large-960h")
 def map_to_array(batch):
     speech, _ = sf.read(batch["file"])