Instructions to use iamcode6/dinov2-l-ccmt-mi300x with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use iamcode6/dinov2-l-ccmt-mi300x with timm:
import timm model = timm.create_model("hf_hub:iamcode6/dinov2-l-ccmt-mi300x", pretrained=True) - Notebooks
- Google Colab
- Kaggle
| precision recall f1-score support | |
| cashew_anthracnose 0.9843 0.9691 0.9766 517 | |
| cashew_gumosis 1.0000 1.0000 1.0000 207 | |
| cashew_healthy 0.9945 0.9986 0.9965 719 | |
| cashew_leaf_miner 0.9741 0.9879 0.9809 494 | |
| cashew_red_rust 0.9969 0.9954 0.9962 651 | |
| cassava_bacterial_blight 0.9829 0.9846 0.9838 1171 | |
| cassava_brown_spot 0.9754 0.9636 0.9695 494 | |
| cassava_green_mite 0.9875 0.9777 0.9825 403 | |
| cassava_healthy 0.9918 1.0000 0.9959 361 | |
| cassava_mosaic 0.9833 0.9944 0.9888 355 | |
| maize_fall_armyworm 0.9934 1.0000 0.9967 150 | |
| maize_grasshoper 1.0000 1.0000 1.0000 274 | |
| maize_healthy 0.9417 1.0000 0.9700 113 | |
| maize_leaf_beetle 1.0000 0.9980 0.9990 497 | |
| maize_leaf_blight 0.8789 0.9004 0.8895 532 | |
| maize_leaf_spot 0.8900 0.8368 0.8626 435 | |
| maize_streak_virus 0.9496 0.9617 0.9556 470 | |
| tomato_healthy 0.9717 0.9917 0.9816 242 | |
| tomato_leaf_blight 0.9553 0.9568 0.9560 625 | |
| tomato_leaf_curl 0.9640 0.9640 0.9640 278 | |
| tomato_septoria_leaf_spot 0.9767 0.9667 0.9717 1171 | |
| tomato_verticulium_wilt 0.9437 0.9591 0.9514 367 | |
| accuracy 0.9706 10526 | |
| macro avg 0.9698 0.9730 0.9713 10526 | |
| weighted avg 0.9706 0.9706 0.9706 10526 | |