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/main/model.safetensors
- Command line
-
hf download hf://Bgeorge/model_dialect/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Bgeorge/model_dialect/resolve/main/model.safetensors
378 MB
- Xet hash:
- 8cdb11a2e7c46472638d7b12ccf50ab9d3c9f4940ac31be2d7f0abe04752b212
- Size of remote file:
- 378 MB
- SHA256:
- 71db49c22023abcfc1985b7b9541fc64a54db22fcf93b08839b432bdd67d8c9a
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