Instructions to use Sjdan/cls_3ep1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/cls_3ep1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, Wav2Vec2ForSpeechClassification processor = AutoProcessor.from_pretrained("Sjdan/cls_3ep1") model = Wav2Vec2ForSpeechClassification.from_pretrained("Sjdan/cls_3ep1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Sjdan/cls_3ep1: direct link, hf CLI and curl.
- Browser
- Download file 1.27 GB
-
https://huggingface.co/Sjdan/cls_3ep1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Sjdan/cls_3ep1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Sjdan/cls_3ep1/resolve/main/pytorch_model.bin
1.27 GB
- Xet hash:
- f01314f77ab88f0f9bdf6107009afbb88a5b5474dcdbc680d844d33183ad17df
- Size of remote file:
- 1.27 GB
- SHA256:
- 3e2b1e121f422bd802c3aa9ae1e83f661ed361edd81c870d96b6260b3db1e998
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