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")# pip install -U transformers accelerate # 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
Download model.safetensors from Bgeorge/model_dialect: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/Bgeorge/model_dialect/resolve/a80fc05ebf44c55c1e84ec8ca9c725be3087d013/model.safetensors
- Command line
-
hf download hf://Bgeorge/model_dialect@a80fc05ebf44c55c1e84ec8ca9c725be3087d013/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Bgeorge/model_dialect/resolve/a80fc05ebf44c55c1e84ec8ca9c725be3087d013/model.safetensors
378 MB
- Xet hash:
- 52a1885994a387e91b4d5e97994ad90903ba0623da17edb1ae2acb608ddd1894
- Size of remote file:
- 378 MB
- SHA256:
- c3e121edc65ab2f7482111d8645f4898220b51186617665387d231184f19ff8f
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