Instructions to use raqibcodes/c2c-checkpoints-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raqibcodes/c2c-checkpoints-v2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("raqibcodes/c2c-checkpoints-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- beeb9727e7cb495cc21e06bbcc245e9d82478b432e2911578b693a08d075eea0
- Size of remote file:
- 5.71 kB
- SHA256:
- d120c92ba91ddf4ca0253a099ee22d2291712c5f091a4855f1d947cb6f6a6059
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.