Instructions to use MicroPhion/wav2vec2-base-lang-id with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MicroPhion/wav2vec2-base-lang-id with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="MicroPhion/wav2vec2-base-lang-id")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("MicroPhion/wav2vec2-base-lang-id") model = AutoModelForAudioClassification.from_pretrained("MicroPhion/wav2vec2-base-lang-id", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c54a9a7057fc0c2f26e65658c957918c0b88c0435bcd3a0aa8c264204d31a136
- Size of remote file:
- 5.3 kB
- SHA256:
- 9c018ba9cfa5d693d7b3be7e8d16d978840625aa099454c40dcd56e471e1a7bf
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