Instructions to use FidelOdok/doa_model_TL3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FidelOdok/doa_model_TL3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="FidelOdok/doa_model_TL3")# pip install -U transformers accelerate # Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("FidelOdok/doa_model_TL3") model = AutoModelForAudioClassification.from_pretrained("FidelOdok/doa_model_TL3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from FidelOdok/doa_model_TL3: direct link, hf CLI and curl.
- Browser
- Download file 345 MB
-
https://huggingface.co/FidelOdok/doa_model_TL3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://FidelOdok/doa_model_TL3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/FidelOdok/doa_model_TL3/resolve/main/pytorch_model.bin
345 MB
- Xet hash:
- 7208de5bf59b8955476eb922c4bfcf129bd432f237f748a02a6c0d69b0a1d57a
- Size of remote file:
- 345 MB
- SHA256:
- b2d259208db93efefe0452fe2c4801bddc84f769d251e3516475532f02146c04
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