Instructions to use mobilint/Swin_B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Mobilint
How to use mobilint/Swin_B with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="Swin_B", 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 ·
bb8f224
1
Parent(s): fc149b0
Move mxq and best_result to aries folder and update gitattributes
Browse files- .gitattributes +1 -0
- aries/best_result.json +1 -0
- aries/swin_b_IMAGENET1K_V1.mxq +3 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.mxq filter=lfs diff=lfs merge=lfs -text
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aries/best_result.json
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{"acc": 0.83254, "timestamp": 1778243945, "checkpoint_dir_name": null, "done": true, "training_iteration": 1, "trial_id": "cccd4729", "date": "2026-05-08_21-39-05", "time_this_iter_s": 3084.4446835517883, "time_total_s": 3084.4446835517883, "pid": 1170387, "hostname": "ae30e054f296", "node_ip": "172.17.0.3", "config": {"percentile": 0.0013103114876514142, "topk": 0.003947159326782156}, "time_since_restore": 3084.4446835517883, "iterations_since_restore": 1, "experiment_tag": "19_percentile=0.0013,topk=0.0039"}
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aries/swin_b_IMAGENET1K_V1.mxq
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version https://git-lfs.github.com/spec/v1
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oid sha256:5d2dba2388483581deb002e461a41410187593455512ba1832c0ca937b48e546
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size 138993628
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