Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use lpcortez/audio_consistency with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lpcortez/audio_consistency with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="lpcortez/audio_consistency")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("lpcortez/audio_consistency") model = AutoModelForAudioClassification.from_pretrained("lpcortez/audio_consistency", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from lpcortez/audio_consistency: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/lpcortez/audio_consistency/resolve/main/training_args.bin
- Command line
-
hf download hf://lpcortez/audio_consistency/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/lpcortez/audio_consistency/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- 9b0834cbdb5e2769ead5c94ca30fb3e9057702d632f7cfb14f4975f815251e6a
- Size of remote file:
- 5.18 kB
- SHA256:
- 936584c6eb9db5942133bccc017a7cc9e674768c959b917b78549462856f98fd
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