Instructions to use mobilint/YOLO11x with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Mobilint
How to use mobilint/YOLO11x with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="YOLO11x", 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 ·
da14c4b
1
Parent(s): 3d55bf3
feat: Add ARIES model artifacts
Browse files- aries/best_result.json +1 -0
- aries/yolo11x.mxq +3 -0
aries/best_result.json
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{"acc": 0.5413598600994441, "timestamp": 1776238822, "checkpoint_dir_name": null, "done": true, "training_iteration": 1, "trial_id": "517f181d", "date": "2026-04-15_16-40-22", "time_this_iter_s": 772.0315079689026, "time_total_s": 772.0315079689026, "pid": 1138275, "hostname": "285e74beb487", "node_ip": "172.17.0.4", "config": {"percentile": 0.00014030556386423213, "topk": 0.026725289766441777}, "time_since_restore": 772.0315079689026, "iterations_since_restore": 1, "experiment_tag": "9_percentile=0.0001,topk=0.0267"}
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aries/yolo11x.mxq
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version https://git-lfs.github.com/spec/v1
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oid sha256:818c5d52942a215655b5e0b0cdefe6c2a09e832c29b80ef12cdb61575d85a8c8
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size 63928350
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