Instructions to use aibtw/circor_wav2vec_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aibtw/circor_wav2vec_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="aibtw/circor_wav2vec_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("aibtw/circor_wav2vec_model") model = AutoModelForAudioClassification.from_pretrained("aibtw/circor_wav2vec_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from aibtw/circor_wav2vec_model: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/aibtw/circor_wav2vec_model/resolve/main/training_args.bin
- Command line
-
hf download hf://aibtw/circor_wav2vec_model/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/aibtw/circor_wav2vec_model/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 58efe9f339ff4df4685ae01bd0313824bc3d52d305f9c2a1277e4227d92e29cb
- Size of remote file:
- 3.96 kB
- SHA256:
- 7c60162c13c78164461ecf1f3d1685a317a41a95433d0593896ed5b126d1d2c7
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