Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use Zarakun/wav2vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Zarakun/wav2vec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Zarakun/wav2vec")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Zarakun/wav2vec") model = AutoModelForAudioClassification.from_pretrained("Zarakun/wav2vec", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Zarakun/wav2vec: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/Zarakun/wav2vec/resolve/main/training_args.bin
- Command line
-
hf download hf://Zarakun/wav2vec/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Zarakun/wav2vec/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- c6c01098bca6f399a9de57cd6c841687d11bb0227272003701af2c38a576bacd
- Size of remote file:
- 5.18 kB
- SHA256:
- 83d53c1fe0f1d6a85680985d9dd4a56ad191a4b305354e673a878051b1c6bce1
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