Instructions to use deadcode99/mistral-billm-token-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deadcode99/mistral-billm-token-classification with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("deadcode99/mistral-billm-token-classification", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a2efa4a7931c9e7b01a2b28fc0683159f82f82626f11add645f5a279fbec0668
- Size of remote file:
- 27.3 MB
- SHA256:
- a1c9abfbce7f47a9948f7ba8a6dd6edb9901291df3d52eb5cef5c39f3f7dccce
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.