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")# pip install -U transformers accelerate # 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
Download training_args.bin from Madronus/MultiLabel_V3: direct link, hf CLI and curl.
- Browser
- Download file 3.52 kB
-
https://huggingface.co/Madronus/MultiLabel_V3/resolve/refs%2Fpr%2F2/training_args.bin
- Command line
-
hf download hf://Madronus/MultiLabel_V3@refs/pr/2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Madronus/MultiLabel_V3/resolve/refs%2Fpr%2F2/training_args.bin
3.52 kB
- Xet hash:
- cee6c2ccd587ad477de67ee7b4cdfc3628d9624761b5e38827cfeac924badc0d
- Size of remote file:
- 3.52 kB
- SHA256:
- 3c3691259f02bb32c46f569ed728b2a26475be36f0ed5686766733e90e1b2c99
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