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 pytorch_model.bin from FidelOdok/doa_model_TL2: direct link, hf CLI and curl.
- Browser
- Download file 345 MB
-
https://huggingface.co/FidelOdok/doa_model_TL2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://FidelOdok/doa_model_TL2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/FidelOdok/doa_model_TL2/resolve/main/pytorch_model.bin
345 MB
- Xet hash:
- 960b4e169e8be70005d808307f465bf4f3defd288193f1eab09642a9dcf32811
- Size of remote file:
- 345 MB
- SHA256:
- dab4671eddf8753708bd4ea8bbef0ed59af3dcfd0732c3331a234f7e7d569d6e
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