Instructions to use mpariente/ConvTasNet_WHAM_sepclean with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Asteroid
How to use mpariente/ConvTasNet_WHAM_sepclean with Asteroid:
from asteroid.models import BaseModel model = BaseModel.from_pretrained("mpariente/ConvTasNet_WHAM_sepclean") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mpariente/ConvTasNet_WHAM_sepclean: direct link, hf CLI and curl.
- Browser
- Download file 20.3 MB
-
https://huggingface.co/mpariente/ConvTasNet_WHAM_sepclean/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mpariente/ConvTasNet_WHAM_sepclean/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mpariente/ConvTasNet_WHAM_sepclean/resolve/main/pytorch_model.bin
20.3 MB
- Xet hash:
- 07f01386b64cf0e627998c4434e1a3db71d7964260fd6c8ffe9e5290ea9019a1
- Size of remote file:
- 20.3 MB
- SHA256:
- db8de6c4d9075c484760dbe6106a544e3cd8f22b69f91868ecabc8b869f9a5a5
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