Instructions to use mobilint/DenseNet201 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Mobilint
How to use mobilint/DenseNet201 with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="DenseNet201", 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
feat: Update DenseNet201 models by replacing the global variant with global4 and global8, modifying multi and single variants, and generalizing .mxq LFS tracking in .gitattributes.
b0e6d42 - Xet hash:
- 478bf09cd2f79aae5180ff9a1fd864e04f24a6bd9c21b91d6cbaf57504474750
- Size of remote file:
- 35.2 MB
- SHA256:
- 11b88b9b17840c838bcb5f4c0b4e424c758d98fbb8ef0098ef437c7f86518540
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.