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wav2vec2-large-960h-lv60-self
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Update README.md

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Patrick von Platen 2021-02-11 13:17:32 +00:00 committed by huggingface-web
parent 71ed25fdc4
commit 75ecb48726
1 changed files with 7 additions and 4 deletions
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README.md
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@ -76,7 +76,7 @@ from jiwer import wer
librispeech_eval = load_dataset("librispeech_asr", "clean", split="test") librispeech_eval = load_dataset("librispeech_asr", "clean", split="test")
model = Wav2Vec2ForCTC.from_pretrained("facebook/wav2vec2-large-960h-lv60-self").to("cuda") model = Wav2Vec2ForCTC.from_pretrained("facebook/wav2vec2-large-960h-lv60-self").to("cuda")
tokenizer = Wav2Vec2Tokenizer.from_pretrained("facebook/wav2vec2-base-960h-lv60-self") tokenizer = Wav2Vec2Tokenizer.from_pretrained("facebook/wav2vec2-large-960h-lv60-self")
def map_to_array(batch): def map_to_array(batch):
speech, _ = sf.read(batch["file"]) speech, _ = sf.read(batch["file"])
@ -86,9 +86,12 @@ def map_to_array(batch):
librispeech_eval = librispeech_eval.map(map_to_array) librispeech_eval = librispeech_eval.map(map_to_array)
def map_to_pred(batch): def map_to_pred(batch):
input_values = tokenizer(batch["speech"], return_tensors="pt", padding="longest").input_values inputs = tokenizer(batch["speech"], return_tensors="pt", padding="longest")
input_values = inputs.input_values.to("cuda")
attention_mask = inputs.attention_mask.to("cuda")
with torch.no_grad(): with torch.no_grad():
logits = model(input_values.to("cuda")).logits logits = model(input_values, attention_mask=attention_mask).logits
predicted_ids = torch.argmax(logits, dim=-1) predicted_ids = torch.argmax(logits, dim=-1)
transcription = tokenizer.batch_decode(predicted_ids) transcription = tokenizer.batch_decode(predicted_ids)
@ -104,4 +107,4 @@ print("WER:", wer(result["text"], result["transcription"]))
| "clean" | "other" | | "clean" | "other" |
|---|---| |---|---|
| 2.2 | 5.2 | | 1.9 | 3.9 |