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
- Xet hash:
- 3b9d946498ca13e4cf174d38a8869f67d12fff04454622a0b38fa3c46f504e7c
- Size of remote file:
- 1.07 GB
- SHA256:
- 55e3aa76d71b3792f1a0a055316c0c205e0697a44778d4a6e6af4fc9994fd93c
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