Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
Safetensors
English
wav2vec2
audio
hf-asr-leaderboard
Eval Results (legacy)
Eval Results
Instructions to use facebook/wav2vec2-base-960h with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/wav2vec2-base-960h with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-base-960h")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("facebook/wav2vec2-base-960h") model = AutoModelForCTC.from_pretrained("facebook/wav2vec2-base-960h") - Notebooks
- Google Colab
- Kaggle
Commit ·
3dfd745
1
Parent(s): 0bc6398
add tf model
Browse files- tf_model.h5 +3 -0
tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:f88fdf86f2388231de92052536f9d769d4a6235e765d8da01b9fc34383db4c0b
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size 377837152
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