Instructions to use AMindToThink/code-detection-confound-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AMindToThink/code-detection-confound-checkpoints with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AMindToThink/code-detection-confound-checkpoints", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ebb0f6e7265cb9f617f88de91257a7cd86a648aff0e903d29edf5259a37eab7
- Size of remote file:
- 504 MB
- SHA256:
- d5e0e8c511d0dd9a30f6bb44eb2cd5e8546a68d6228e82b9a1e17fbc6d69584e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.