Instructions to use knarayan/model_cspm_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use knarayan/model_cspm_lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("knarayan/model_cspm_lora", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5203b0387525647bb9b580f3de1831f272cb6c7c85c9b7cdd3d9716e78600c15
- Size of remote file:
- 5.62 kB
- SHA256:
- 28d3213c0fa1ef013add97244f8fe755e92bbdcb2c73b054f0dd6cb771428797
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.