Instructions to use voidful/lcodec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidful/lcodec with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("voidful/lcodec", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 92e4f1c70067a68d2fdec65d15690c03ef365d620a1ce3a22ff4808a9c73bf48
- Size of remote file:
- 491 MB
- SHA256:
- 200a1a3f425d3d4591c315c88df67b432909ac18a2d2f9f6c6bc59a6c1ceda20
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.