Instructions to use anton-l/wav2vec2-base-finetuned-ks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anton-l/wav2vec2-base-finetuned-ks with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anton-l/wav2vec2-base-finetuned-ks")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anton-l/wav2vec2-base-finetuned-ks") model = AutoModelForAudioClassification.from_pretrained("anton-l/wav2vec2-base-finetuned-ks", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from anton-l/wav2vec2-base-finetuned-ks: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/anton-l/wav2vec2-base-finetuned-ks/resolve/main/training_args.bin
- Command line
-
hf download hf://anton-l/wav2vec2-base-finetuned-ks/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/anton-l/wav2vec2-base-finetuned-ks/resolve/main/training_args.bin
2.86 kB
- Xet hash:
- 241e86c80c28a6a4dca8de8f9ed9dea12ab95ba567d508429b05ad092a572833
- Size of remote file:
- 2.86 kB
- SHA256:
- a21bee661171c7b2c6b8af568b34bf0e1711c5f29fc38ca66e28344cbe9b73b3
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