Instructions to use gustproof/dnbr-tagger-preview1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use gustproof/dnbr-tagger-preview1 with timm:
import timm model = timm.create_model("hf_hub:gustproof/dnbr-tagger-preview1", pretrained=True) - Transformers
How to use gustproof/dnbr-tagger-preview1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="gustproof/dnbr-tagger-preview1") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("gustproof/dnbr-tagger-preview1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
A lightweight multilabel classifier trained on an arbitrary subset of nyanko7/danbooru2023. Trained for ~40M samples at native resolution ~238x238. Decent performance for its size.
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