Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use itsmefaiz/audio_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use itsmefaiz/audio_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="itsmefaiz/audio_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("itsmefaiz/audio_classification") model = AutoModelForAudioClassification.from_pretrained("itsmefaiz/audio_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from itsmefaiz/audio_classification: direct link, hf CLI and curl.
- Browser
- Download file 4.6 kB
-
https://huggingface.co/itsmefaiz/audio_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://itsmefaiz/audio_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/itsmefaiz/audio_classification/resolve/main/training_args.bin
4.6 kB
- Xet hash:
- badeacc2c28c8ec4080cc8af96d850674c4d358971d8eb67c615418f8d97919d
- Size of remote file:
- 4.6 kB
- SHA256:
- 48aa59941e1fd71f7b01b2a94b99f34e789ff95b8a7c31cf01759746429e920b
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