Instructions to use Brokette/wav2vec2-base-timit-test5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Brokette/wav2vec2-base-timit-test5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Brokette/wav2vec2-base-timit-test5")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Brokette/wav2vec2-base-timit-test5") model = AutoModelForCTC.from_pretrained("Brokette/wav2vec2-base-timit-test5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5318224f9f27dd3d7770b7e6c2e6db6ecb3a856d5cb4839357cc7a40dd945b12
- Size of remote file:
- 378 MB
- SHA256:
- 4db61b0548b01d945a7f0dcc1c701d2f63d2febb7d831bdc7e9da16bfba17161
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