Instructions to use Sjdan/cls_asr_7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/cls_asr_7 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, Wav2Vec2ForSpeechClassification processor = AutoProcessor.from_pretrained("Sjdan/cls_asr_7") model = Wav2Vec2ForSpeechClassification.from_pretrained("Sjdan/cls_asr_7", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Sjdan/cls_asr_7: direct link, hf CLI and curl.
- Browser
- Download file 1.27 GB
-
https://huggingface.co/Sjdan/cls_asr_7/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Sjdan/cls_asr_7/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Sjdan/cls_asr_7/resolve/main/pytorch_model.bin
1.27 GB
- Xet hash:
- fd2422b3a2d0e9f42e049d3e0cd4b2478a9146587c9e0d431a64f1a9605ee096
- Size of remote file:
- 1.27 GB
- SHA256:
- 12451e512a55df90753e75a6bb1105a5ab5fde654f6a37f324e1efa824eed96a
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