Instructions to use Sjdan/C3_2_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/C3_2_1 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, Wav2Vec2ForSpeechClassification processor = AutoProcessor.from_pretrained("Sjdan/C3_2_1") model = Wav2Vec2ForSpeechClassification.from_pretrained("Sjdan/C3_2_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Sjdan/C3_2_1: direct link, hf CLI and curl.
- Browser
- Download file 1.27 GB
-
https://huggingface.co/Sjdan/C3_2_1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Sjdan/C3_2_1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Sjdan/C3_2_1/resolve/main/pytorch_model.bin
1.27 GB
- Xet hash:
- f5f20ecdd47f66629c232da980f2cd370b9c12adbcc016ecd4344506be39d3b1
- Size of remote file:
- 1.27 GB
- SHA256:
- b46b99fd517822722db5d17d4166bbb938ca78884b18a695c3dd799d7952dace
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