Instructions to use anton-l/wav2vec2-base-keyword-spotting with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anton-l/wav2vec2-base-keyword-spotting with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anton-l/wav2vec2-base-keyword-spotting")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anton-l/wav2vec2-base-keyword-spotting") model = AutoModelForAudioClassification.from_pretrained("anton-l/wav2vec2-base-keyword-spotting", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from anton-l/wav2vec2-base-keyword-spotting: direct link, hf CLI and curl.
- Browser
- Download file 2.99 kB
-
https://huggingface.co/anton-l/wav2vec2-base-keyword-spotting/resolve/main/training_args.bin
- Command line
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hf download hf://anton-l/wav2vec2-base-keyword-spotting/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/anton-l/wav2vec2-base-keyword-spotting/resolve/main/training_args.bin
2.99 kB
- Xet hash:
- 9365344b3fbf35568f06b9e906d9dc99487c03f9ec6d4f3b7ba7f3491ca591d3
- Size of remote file:
- 2.99 kB
- SHA256:
- 2a81868308e2363a3d278b8de1b6e37b85e78b4d51d5338b94d5de25a6dcafe0
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