Instructions to use mobilint/ConvNeXt_Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Mobilint
How to use mobilint/ConvNeXt_Base with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="ConvNeXt_Base", 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
Prepare board-specific Aries Vision artifacts
Browse files
aries-rb/best_result.json
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{"acc": 0.8394, "timestamp": 1776185122, "checkpoint_dir_name": null, "done": true, "training_iteration": 1, "trial_id": "d9d0f31e", "date": "2026-04-15_01-45-22", "time_this_iter_s": 2413.846477508545, "time_total_s": 2413.846477508545, "pid": 256557, "hostname": "ae30e054f296", "node_ip": "172.17.0.3", "config": {"percentile": 0.0005375928727318541, "topk": 0.002090818643447934}, "time_since_restore": 2413.846477508545, "iterations_since_restore": 1, "experiment_tag": "14_percentile=0.0005,topk=0.0021"}
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