Instructions to use FidelOdok/doa_model_TL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FidelOdok/doa_model_TL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="FidelOdok/doa_model_TL")# pip install -U transformers accelerate # Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("FidelOdok/doa_model_TL") model = AutoModelForAudioClassification.from_pretrained("FidelOdok/doa_model_TL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from FidelOdok/doa_model_TL: direct link, hf CLI and curl.
- Browser
- Download file 345 MB
-
https://huggingface.co/FidelOdok/doa_model_TL/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://FidelOdok/doa_model_TL/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/FidelOdok/doa_model_TL/resolve/main/pytorch_model.bin
345 MB
- Xet hash:
- 7ac947bff4cef7ba473f043b5dedd47d8af1e6567ceebb2aa315e99b19e2d966
- Size of remote file:
- 345 MB
- SHA256:
- 8ec477c789077dc36c75f42cd394c830f797dce8c6ab3114aba670fc7bbb66e9
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