Transformers
TensorBoard
Safetensors
pyannet
speaker-diarization
speaker-segmentation
Generated from Trainer
Instructions to use OpenLiliO/diarization-fr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenLiliO/diarization-fr with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenLiliO/diarization-fr", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0a4201ecb2488c16d272745e308918dead0ba2457ce007ee287048deacaff5f
- Size of remote file:
- 5.37 kB
- SHA256:
- 6be4d81c9d0f6280420aa189c8ea141084ee9f7c4e77cd4c75bab54e8d08f536
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.