Instructions to use mobilint/EfficientNet_V2_M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Mobilint
How to use mobilint/EfficientNet_V2_M with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="EfficientNet_V2_M", 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 ·
5dbe355
1
Parent(s): 8119212
Add aries results and configure git lfs
Browse files- .gitattributes +1 -0
- aries/best_result.json +1 -0
- aries/efficientnet_v2_m_IMAGENET1K_V1.mxq +3 -0
.gitattributes
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aries/best_result.json
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{"acc": 0.81632, "timestamp": 1777077005, "checkpoint_dir_name": null, "done": true, "training_iteration": 1, "trial_id": "1afe556d", "date": "2026-04-25_09-30-05", "time_this_iter_s": 3109.510190963745, "time_total_s": 3109.510190963745, "pid": 2751255, "hostname": "ae30e054f296", "node_ip": "172.17.0.3", "config": {"percentile": 0.0003916453677485466, "topk": 0.001177061246283976}, "time_since_restore": 3109.510190963745, "iterations_since_restore": 1, "experiment_tag": "8_percentile=0.0004,topk=0.0012"}
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aries/efficientnet_v2_m_IMAGENET1K_V1.mxq
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version https://git-lfs.github.com/spec/v1
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oid sha256:7500c260c70eda762685b7149411f80d3908b8dd414cbedb20ee449df86919b8
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size 68638094
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