Instructions to use learningdude/wav2vec2-base-sound2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use learningdude/wav2vec2-base-sound2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="learningdude/wav2vec2-base-sound2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("learningdude/wav2vec2-base-sound2") model = AutoModelForAudioClassification.from_pretrained("learningdude/wav2vec2-base-sound2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from learningdude/wav2vec2-base-sound2: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/learningdude/wav2vec2-base-sound2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://learningdude/wav2vec2-base-sound2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/learningdude/wav2vec2-base-sound2/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- cd21f0aceaaf6c547a92b3743bd49cdc43c1534b39869c055821c190f3640a30
- Size of remote file:
- 378 MB
- SHA256:
- 9a5d6a52bff16f8d1383916efca2a116103d9c1e21f9eb4850c89fac14b0d785
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