Instructions to use mobilint/YOLOv10b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Mobilint
How to use mobilint/YOLOv10b with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="YOLOv10b", model_type="DEFAULT", model_path="", core_mode="global8", ) try: image = model.preprocess("path/to/image.jpg") output = model(image) result = model.postprocess(output) finally: model.dispose() - Notebooks
- Google Colab
- Kaggle
Commit ·
808c341
1
Parent(s): f25353f
feat: Add ARIES model artifacts
Browse files- aries/best_result.json +1 -0
- aries/yolov10b.mxq +3 -0
aries/best_result.json
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{"acc": 0.5152454516551552, "timestamp": 1776409576, "checkpoint_dir_name": null, "done": true, "training_iteration": 1, "trial_id": "697d5192", "date": "2026-04-17_16-06-16", "time_this_iter_s": 510.37539434432983, "time_total_s": 510.37539434432983, "pid": 1855105, "hostname": "285e74beb487", "node_ip": "172.17.0.4", "config": {"percentile": 0.002537997547747607, "topk": 0.009343883993004688}, "time_since_restore": 510.37539434432983, "iterations_since_restore": 1, "experiment_tag": "18_percentile=0.0025,topk=0.0093"}
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aries/yolov10b.mxq
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version https://git-lfs.github.com/spec/v1
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oid sha256:83114143bf6fdb0f72ee637938a8f1f6c9d49432b9fd87f5421b159ad2cd612d
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size 22483131
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