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:
- 0a2cdba8057adaad772282e66268ac2ae5e704cd9f548112a655c059ae762a08
- Size of remote file:
- 96.4 MB
- SHA256:
- 0addcdfd42dd82b5409d02fcbf36098a69ab47a0503093a731fa75e19d06ac2d
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