Instructions to use alg166/checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alg166/checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="alg166/checkpoints")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("alg166/checkpoints") model = AutoModelForAudioClassification.from_pretrained("alg166/checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from alg166/checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 33.2 MB
-
https://huggingface.co/alg166/checkpoints/resolve/main/model.safetensors
- Command line
-
hf download hf://alg166/checkpoints/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/alg166/checkpoints/resolve/main/model.safetensors
33.2 MB
- Xet hash:
- b1f5906f51dc71cadaf5bbdc977d2f8dbfe75137b8e4b827589f832937d4d5b8
- Size of remote file:
- 33.2 MB
- SHA256:
- 7c19e501f0ac2eec5b7108862c80440e9f0c5cece09c641aaf0c17f850fbbb90
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