Instructions to use mobilint/EfficientNet_B6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Mobilint
How to use mobilint/EfficientNet_B6 with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="EfficientNet_B6", 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 ·
25bb493
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Parent(s): c0230b5
Add aries results and configure git lfs
Browse files- .gitattributes +1 -0
- aries/best_result.json +1 -0
- aries/efficientnet_b6_IMAGENET1K_V1.mxq +3 -0
.gitattributes
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aries/best_result.json
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{"acc": 0.82426, "timestamp": 1776793891, "checkpoint_dir_name": null, "done": true, "training_iteration": 1, "trial_id": "81651d0f", "date": "2026-04-22_02-51-31", "time_this_iter_s": 3559.448047399521, "time_total_s": 3559.448047399521, "pid": 1484248, "hostname": "ae30e054f296", "node_ip": "172.17.0.3", "config": {"percentile": 0.003467826695044171, "topk": 0.001037237194759298}, "time_since_restore": 3559.448047399521, "iterations_since_restore": 1, "experiment_tag": "12_percentile=0.0035,topk=0.0010"}
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aries/efficientnet_b6_IMAGENET1K_V1.mxq
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version https://git-lfs.github.com/spec/v1
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oid sha256:e527356b047173833c1bb3458c9ab596af523c720a86a1944ae15c0756669be6
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size 58251101
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