Instructions to use mobilint/YOLO12l with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Mobilint
How to use mobilint/YOLO12l with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="YOLO12l", 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 ·
b6d3fda
1
Parent(s): ab2e741
feat: Add ARIES model artifacts
Browse files- aries/best_result.json +1 -0
- aries/yolo12l.mxq +3 -0
aries/best_result.json
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{"acc": 0.5319976432258331, "timestamp": 1776262761, "checkpoint_dir_name": null, "done": true, "training_iteration": 1, "trial_id": "14d27f81", "date": "2026-04-15_23-19-21", "time_this_iter_s": 1432.9041938781738, "time_total_s": 1432.9041938781738, "pid": 1211257, "hostname": "285e74beb487", "node_ip": "172.17.0.4", "config": {"percentile": 0.00020899725856185833, "topk": 0.0132932044286133}, "time_since_restore": 1432.9041938781738, "iterations_since_restore": 1, "experiment_tag": "11_percentile=0.0002,topk=0.0133"}
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aries/yolo12l.mxq
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version https://git-lfs.github.com/spec/v1
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oid sha256:c6bc67ae7ba10edae2eb0c7de4fd1e904949d1679f509397149b2ac333849d4d
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size 38395609
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