Instructions to use davanstrien/red-squirrel-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/red-squirrel-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="davanstrien/red-squirrel-detector")# Load model directly from transformers import AutoTokenizer, AutoModelForObjectDetection tokenizer = AutoTokenizer.from_pretrained("davanstrien/red-squirrel-detector") model = AutoModelForObjectDetection.from_pretrained("davanstrien/red-squirrel-detector") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 30.0, | |
| "eval_loss": 0.7586857080459595, | |
| "eval_map": 0.8614, | |
| "eval_map_50": 0.9087, | |
| "eval_map_75": 0.8839, | |
| "eval_map_class_0": 0.8614, | |
| "eval_map_large": 0.8901, | |
| "eval_map_medium": 0.63, | |
| "eval_map_small": 0.0, | |
| "eval_mar_1": 0.7528, | |
| "eval_mar_10": 0.8876, | |
| "eval_mar_100": 0.9441, | |
| "eval_mar_100_class_0": 0.9441, | |
| "eval_mar_large": 0.9653, | |
| "eval_mar_medium": 0.7769, | |
| "eval_mar_small": 0.0, | |
| "eval_runtime": 6.4866, | |
| "eval_samples_per_second": 19.733, | |
| "eval_steps_per_second": 2.467 | |
| } |