Instructions to use PRATYUSH-BHARDWAJ/Cortex_A_0.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PRATYUSH-BHARDWAJ/Cortex_A_0.5 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("PRATYUSH-BHARDWAJ/Cortex_A_0.5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
- Xet hash:
- 1419ca199d0cf2d18bc7179a39f61ff8300d05c0720b8496c715d2771c99a35d
- Size of remote file:
- 621 MB
- SHA256:
- 1726837a362882aad5022a2eb1997a16b7cfa5aba0001bb769e791f71606704d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.