Instructions to use laura63/wav2vec2-base-finetuned-ks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use laura63/wav2vec2-base-finetuned-ks with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="laura63/wav2vec2-base-finetuned-ks")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("laura63/wav2vec2-base-finetuned-ks") model = AutoModelForAudioClassification.from_pretrained("laura63/wav2vec2-base-finetuned-ks", device_map="auto") - Notebooks
- Google Colab
- Kaggle
wav2vec2-base-finetuned-ks / runs /Jul03_17-19-33_71427e3f87d4 /events.out.tfevents.1688409883.71427e3f87d4.16345.4
Download runs/Jul03_17-19-33_71427e3f87d4/events.out.tfevents.1688409883.71427e3f87d4.16345.4 from laura63/wav2vec2-base-finetuned-ks: direct link, hf CLI and curl.
- Browser
- Download file 457 Bytes
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https://huggingface.co/laura63/wav2vec2-base-finetuned-ks/resolve/ee93471cfa5b0a8a2f2d28f88391955f3abfe3c4/runs/Jul03_17-19-33_71427e3f87d4/events.out.tfevents.1688409883.71427e3f87d4.16345.4
- Command line
-
hf download hf://laura63/wav2vec2-base-finetuned-ks@ee93471cfa5b0a8a2f2d28f88391955f3abfe3c4/runs/Jul03_17-19-33_71427e3f87d4/events.out.tfevents.1688409883.71427e3f87d4.16345.4
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curl -L -o events.out.tfevents.1688409883.71427e3f87d4.16345.4 https://huggingface.co/laura63/wav2vec2-base-finetuned-ks/resolve/ee93471cfa5b0a8a2f2d28f88391955f3abfe3c4/runs/Jul03_17-19-33_71427e3f87d4/events.out.tfevents.1688409883.71427e3f87d4.16345.4
457 Bytes
- Xet hash:
- ac58202a99c40ec6429b2a4eac005573f43a649d0486392e5a094545a3c19daf
- Size of remote file:
- 457 Bytes
- SHA256:
- 5a4421c6e83a720acd4387b4e22dcf24d2810a5b7ca0e911d8ecf51e778d71a7
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