Instructions to use iloncka/culico-net-cls-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- fastai
How to use iloncka/culico-net-cls-v1 with fastai:
from huggingface_hub import from_pretrained_fastai learn = from_pretrained_fastai("iloncka/culico-net-cls-v1") - timm
How to use iloncka/culico-net-cls-v1 with timm:
import timm model = timm.create_model("hf_hub:iloncka/culico-net-cls-v1", pretrained=True) - Transformers
How to use iloncka/culico-net-cls-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="iloncka/culico-net-cls-v1") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("iloncka/culico-net-cls-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3f2dc8a29037f10e9bf3a8e31bc31ddc724c48e0bf6b944f28842c69ac93b7e5
- Size of remote file:
- 99.3 MB
- SHA256:
- 1719be673435fa3b1c753f648c6e40b8014d48574b621719d56333066c9e2891
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