Instructions to use mobilint/VGG11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Mobilint
How to use mobilint/VGG11 with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="VGG11", 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
Kanybek Asanbekov commited on
Commit ·
80c507e
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Parent(s): b7ec301
Move mxq and best_result to aries folder and update gitattributes
Browse files- aries/best_result.json +1 -0
- aries/vgg11_IMAGENET1K_V1.mxq +3 -0
aries/best_result.json
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{"acc": 0.68706, "timestamp": 1778337945, "checkpoint_dir_name": null, "done": true, "training_iteration": 1, "trial_id": "e9554c2b", "date": "2026-05-09_23-45-45", "time_this_iter_s": 583.4316008090973, "time_total_s": 583.4316008090973, "pid": 1269361, "hostname": "ae30e054f296", "node_ip": "172.17.0.3", "config": {"percentile": 0.000489992397525748, "topk": 0.0015808136209885476}, "time_since_restore": 583.4316008090973, "iterations_since_restore": 1, "experiment_tag": "6_percentile=0.0005,topk=0.0016"}
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aries/vgg11_IMAGENET1K_V1.mxq
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version https://git-lfs.github.com/spec/v1
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oid sha256:671913dcfb5cdd24c09814696707e22b1167d8ca695101ae2e79cece23873b49
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size 133293607
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