Instructions to use fitlemon/language_detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fitlemon/language_detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="fitlemon/language_detector")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("fitlemon/language_detector") model = AutoModelForAudioClassification.from_pretrained("fitlemon/language_detector") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4fceba95cf42fbb5a7a9de65fb6d0072163eadb58bb90d7408d4ba6a607ebf48
- Size of remote file:
- 353 MB
- SHA256:
- 06a36a47f14fa1d05e3d79a712ac9f4a46a3757bc7689a350b799cfb86e8efa3
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