Instructions to use nonl/dfine-cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nonl/dfine-cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="nonl/dfine-cppe5")# Load model directly from transformers import AutoTokenizer, AutoModelForObjectDetection tokenizer = AutoTokenizer.from_pretrained("nonl/dfine-cppe5") model = AutoModelForObjectDetection.from_pretrained("nonl/dfine-cppe5") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 300.0, | |
| "test_loss": 4.271916389465332, | |
| "test_map": 0.2447, | |
| "test_map_50": 0.3449, | |
| "test_map_75": 0.2657, | |
| "test_map_Coverall": 0.5564, | |
| "test_map_Face_Shield": 0.2347, | |
| "test_map_Gloves": 0.0469, | |
| "test_map_Goggles": 0.181, | |
| "test_map_Mask": 0.2045, | |
| "test_map_large": 0.2457, | |
| "test_map_medium": 0.1547, | |
| "test_map_small": 0.288, | |
| "test_mar_1": 0.2186, | |
| "test_mar_10": 0.5799, | |
| "test_mar_100": 0.6928, | |
| "test_mar_100_Coverall": 0.8051, | |
| "test_mar_100_Face_Shield": 0.8176, | |
| "test_mar_100_Gloves": 0.5458, | |
| "test_mar_100_Goggles": 0.6172, | |
| "test_mar_100_Mask": 0.6784, | |
| "test_mar_large": 0.8429, | |
| "test_mar_medium": 0.5042, | |
| "test_mar_small": 0.5792, | |
| "test_runtime": 0.7065, | |
| "test_samples_per_second": 41.05, | |
| "test_steps_per_second": 5.662 | |
| } |