Automatic Speech Recognition
Transformers
PyTorch
English
wav2vec2
audio
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use jonatasgrosman/wav2vec2-large-english with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonatasgrosman/wav2vec2-large-english with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/wav2vec2-large-english")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/wav2vec2-large-english") model = AutoModelForCTC.from_pretrained("jonatasgrosman/wav2vec2-large-english") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb80f4180200e9d709f4800933784c34098caf1171c1563222b485e6e63270cc
- Size of remote file:
- 1.26 GB
- SHA256:
- 53a299003920a2ebacc857bf3f0c2706c06cc88e6c45924e4aa4cb5b9fb0c04d
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