Instructions to use Sjdan/switch_cls_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/switch_cls_2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, Wav2Vec2ForSpeechClassification processor = AutoProcessor.from_pretrained("Sjdan/switch_cls_2") model = Wav2Vec2ForSpeechClassification.from_pretrained("Sjdan/switch_cls_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Sjdan/switch_cls_2: direct link, hf CLI and curl.
- Browser
- Download file 1.27 GB
-
https://huggingface.co/Sjdan/switch_cls_2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Sjdan/switch_cls_2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Sjdan/switch_cls_2/resolve/main/pytorch_model.bin
1.27 GB
- Xet hash:
- c71543ea3b5f7a12c53ccdcadb89de3b565e2e39678e13d09aea7496b8c0d0b6
- Size of remote file:
- 1.27 GB
- SHA256:
- e607f796629614a070153f3c7ae473d8d7e686fad6337dd282f250ec9fb520d7
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