Instructions to use oosawy/wav2vec2-base-timit-phoneme with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use oosawy/wav2vec2-base-timit-phoneme with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="oosawy/wav2vec2-base-timit-phoneme")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("oosawy/wav2vec2-base-timit-phoneme") model = AutoModelForCTC.from_pretrained("oosawy/wav2vec2-base-timit-phoneme", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 99327b6dfd3314110ec49ed58a2eaa9e62f79f374fc0b63a9132015db8721abd
- Size of remote file:
- 5.84 kB
- SHA256:
- 831394637559bd950fd9cbcd375e22b70cfecc9980b34fe2240da0500190b8d8
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