Instructions to use karthi12/test-hubert-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use karthi12/test-hubert-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="karthi12/test-hubert-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("karthi12/test-hubert-model") model = AutoModelForAudioClassification.from_pretrained("karthi12/test-hubert-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from karthi12/test-hubert-model: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/karthi12/test-hubert-model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://karthi12/test-hubert-model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/karthi12/test-hubert-model/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- 135031f44eda4ad6a7b70cba0366dbe7def6995a221dfed4c2812204e6b10b2a
- Size of remote file:
- 378 MB
- SHA256:
- 68e558f91663f9b64103e431a550923465879b9b018d4be4b0a3d15d0bda100e
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