Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
English
speech_to_text
audio
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use facebook/s2t-large-librispeech-asr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/s2t-large-librispeech-asr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="facebook/s2t-large-librispeech-asr")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("facebook/s2t-large-librispeech-asr") model = AutoModelForSpeechSeq2Seq.from_pretrained("facebook/s2t-large-librispeech-asr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
#2
by Sharathhebbar24 - opened
README.md
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@@ -98,7 +98,7 @@ input_features = processor(
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sampling_rate=16_000,
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return_tensors="pt"
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).input_features # Batch size 1
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-
generated_ids = model.generate(
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transcription = processor.batch_decode(generated_ids)
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```
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sampling_rate=16_000,
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return_tensors="pt"
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).input_features # Batch size 1
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+
generated_ids = model.generate(input_features)
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transcription = processor.batch_decode(generated_ids)
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```
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