Instructions to use FidelOdok/doa_model_TL2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FidelOdok/doa_model_TL2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="FidelOdok/doa_model_TL2")# pip install -U transformers accelerate # Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("FidelOdok/doa_model_TL2") model = AutoModelForAudioClassification.from_pretrained("FidelOdok/doa_model_TL2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from FidelOdok/doa_model_TL2: direct link, hf CLI and curl.
- Browser
- Download file 3.58 kB
-
https://huggingface.co/FidelOdok/doa_model_TL2/resolve/main/training_args.bin
- Command line
-
hf download hf://FidelOdok/doa_model_TL2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/FidelOdok/doa_model_TL2/resolve/main/training_args.bin
3.58 kB
- Xet hash:
- 3fae96a2c5ef7f6f45491ef4829c1e99f278f9942cbf15bebd3b8637ac710212
- Size of remote file:
- 3.58 kB
- SHA256:
- 65ab869cc1c9c9f6744e4325523c63a10cbce1db31c54f24f273363a10e96caf
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