Instructions to use Abhiram4/AnimeCharacterClassifierMark1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Abhiram4/AnimeCharacterClassifierMark1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Abhiram4/AnimeCharacterClassifierMark1") 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("Abhiram4/AnimeCharacterClassifierMark1") model = AutoModelForImageClassification.from_pretrained("Abhiram4/AnimeCharacterClassifierMark1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Abhiram4/AnimeCharacterClassifierMark1: direct link, hf CLI and curl.
- Browser
- Download file 344 MB
-
https://huggingface.co/Abhiram4/AnimeCharacterClassifierMark1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Abhiram4/AnimeCharacterClassifierMark1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Abhiram4/AnimeCharacterClassifierMark1/resolve/main/pytorch_model.bin
344 MB
- Xet hash:
- 9ab21107073051904be73012032ae2b7666e5eb372a978071259dce0ac550db5
- Size of remote file:
- 344 MB
- SHA256:
- 1f6be57a3a6d275388da2ec761d09c9bf2aa1037042c8f4ac544ba4be48db72d
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