Instructions to use Madronus/MultiLabel_V3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Madronus/MultiLabel_V3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Madronus/MultiLabel_V3") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Madronus/MultiLabel_V3") model = AutoModelForImageClassification.from_pretrained("Madronus/MultiLabel_V3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8fee3ef74cf8fd37167b1e76a7a3beef40cc3a20b60330325e5f81e15828c7ef
- Size of remote file:
- 343 MB
- SHA256:
- c53256229300f837cdc6d903b80286b43d283c5eda78cf6edf837f9c6715c964
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