Instructions to use mobilint/VGG16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Mobilint
How to use mobilint/VGG16 with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="VGG16", 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 ·
0e7619c
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Parent(s): d4dffbc
Move mxq and best_result to aries folder and update gitattributes
Browse files- aries/best_result.json +1 -0
- aries/vgg16_IMAGENET1K_V1.mxq +3 -0
aries/best_result.json
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{"acc": 0.71526, "timestamp": 1778396066, "checkpoint_dir_name": null, "done": true, "training_iteration": 1, "trial_id": "c1f38d8f", "date": "2026-05-10_15-54-26", "time_this_iter_s": 659.8869829177856, "time_total_s": 659.8869829177856, "pid": 1363284, "hostname": "ae30e054f296", "node_ip": "172.17.0.3", "config": {"percentile": 0.0041791364071339454, "topk": 0.02524108320384706}, "time_since_restore": 659.8869829177856, "iterations_since_restore": 1, "experiment_tag": "20_percentile=0.0042,topk=0.0252"}
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aries/vgg16_IMAGENET1K_V1.mxq
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version https://git-lfs.github.com/spec/v1
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oid sha256:f26c5dbabeb980fdf916b5d68c472436fc7fb16fea7a39cb297270507ce517b4
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size 138881322
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