Instructions to use PurCL/codeart-26m-mfc-3f-100c with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PurCL/codeart-26m-mfc-3f-100c with Transformers:
# Load model directly from transformers import CodeArtForMultipleSequenceClassification model = CodeArtForMultipleSequenceClassification.from_pretrained("PurCL/codeart-26m-mfc-3f-100c", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 334d2c4ca49e5c2eabc05f850846bd463bb2c942ad1d5197337d8b244eb77bd0
- Size of remote file:
- 877 MB
- SHA256:
- e980d82c80ed7e2a5e7122078ab6c2ef3781a1fed0b19406464aa775439a3bff
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.