Instructions to use chrisjay/afrospeech-wav2vec-gax with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chrisjay/afrospeech-wav2vec-gax with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="chrisjay/afrospeech-wav2vec-gax")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("chrisjay/afrospeech-wav2vec-gax") model = AutoModelForAudioClassification.from_pretrained("chrisjay/afrospeech-wav2vec-gax", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc51ee51eec72a2dc854d55fadb058ab74b09953eac004718e07bac6e0fca1f8
- Size of remote file:
- 378 MB
- SHA256:
- c60065e55d7aaeb42e56c22f6b1d8044ed75212691ce9b345b033b8125d33653
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