Instructions to use Bgeorge/model_dialect with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bgeorge/model_dialect with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Bgeorge/model_dialect")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Bgeorge/model_dialect") model = AutoModelForAudioClassification.from_pretrained("Bgeorge/model_dialect", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 493575bd6538c8b974e1d449781060e2d792501376002873b8b957f6badb7b44
- Size of remote file:
- 5.3 kB
- SHA256:
- e63bd8478aa65cc5015d363fdf8be44ac7f2339caf3a6cb5823e67acec858f10
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