Instructions to use salixc/dielect_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use salixc/dielect_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="salixc/dielect_classification_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("salixc/dielect_classification_model") model = AutoModelForAudioClassification.from_pretrained("salixc/dielect_classification_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from salixc/dielect_classification_model: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/salixc/dielect_classification_model/resolve/main/training_args.bin
- Command line
-
hf download hf://salixc/dielect_classification_model/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/salixc/dielect_classification_model/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 11a4b4db399514947aa6114788253b42c5cb6fa3212686fea221f698bd70858f
- Size of remote file:
- 5.24 kB
- SHA256:
- 628cb140eed1f829033294664ed7e3a6d52873192cc49c69f0283f692a6cbeb0
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