Instructions to use Sjdan/switch_cls_2_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/switch_cls_2_2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, Wav2Vec2ForSpeechClassification processor = AutoProcessor.from_pretrained("Sjdan/switch_cls_2_2") model = Wav2Vec2ForSpeechClassification.from_pretrained("Sjdan/switch_cls_2_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Sjdan/switch_cls_2_2: direct link, hf CLI and curl.
- Browser
- Download file 1.27 GB
-
https://huggingface.co/Sjdan/switch_cls_2_2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Sjdan/switch_cls_2_2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Sjdan/switch_cls_2_2/resolve/main/pytorch_model.bin
1.27 GB
- Xet hash:
- a84d86b5c8467e5bd432b61c9329e9073bd8955c59db60f03bc05b7a0a9f1dc9
- Size of remote file:
- 1.27 GB
- SHA256:
- c89c72584df66226f85b62f1435f9f6b8dcdccc6b115b31c515d255c0e56d0e8
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