Instructions to use mobilint/DenseNet121 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Mobilint
How to use mobilint/DenseNet121 with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="DenseNet121", 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 ·
c9f55a9
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Parent(s): 97ccdec
Add aries results and fix .gitattributes order
Browse files
aries/best_result.json
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{"acc": 0.7432, "timestamp": 1776391328, "checkpoint_dir_name": null, "done": true, "training_iteration": 1, "trial_id": "55b69f1c", "date": "2026-04-17_11-02-08", "time_this_iter_s": 843.0332050323486, "time_total_s": 843.0332050323486, "pid": 394962, "hostname": "ae30e054f296", "node_ip": "172.17.0.3", "config": {"percentile": 0.004854364294351201, "topk": 0.006548923044954437}, "time_since_restore": 843.0332050323486, "iterations_since_restore": 1, "experiment_tag": "9_percentile=0.0049,topk=0.0065"}
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aries/densenet121_IMAGENET1K_V1.mxq
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version https://git-lfs.github.com/spec/v1
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oid sha256:d5900247fa445ae9ae7c4b16043120ceb5bb62a9ab815dfae045a71da42dc273
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size 15110626
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