Instructions to use maurice-fp/ModelReuse-train.mbnetv2.Flower102-prune.0_8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use maurice-fp/ModelReuse-train.mbnetv2.Flower102-prune.0_8 with timm:
import timm model = timm.create_model("hf_hub:maurice-fp/ModelReuse-train.mbnetv2.Flower102-prune.0_8", pretrained=True) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 32a57a6ce1cc979935eafad0e144f00f2ce08af52aabcb35746b2d5d535cf0d8
- Size of remote file:
- 9.66 MB
- SHA256:
- e7168596ccabb05e9fec4bae089fdab30c5034e3f2da4570ad9beca26db24951
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