Instructions to use Abhiram4/AnimeCharacterClassifierMark2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Abhiram4/AnimeCharacterClassifierMark2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Abhiram4/AnimeCharacterClassifierMark2") 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("Abhiram4/AnimeCharacterClassifierMark2") model = AutoModelForImageClassification.from_pretrained("Abhiram4/AnimeCharacterClassifierMark2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9459d7642a9699685fb2bee3a4d274d833101c8983fe0c86876e70e69262196c
- Size of remote file:
- 4.09 kB
- SHA256:
- 7042505c17387e224b0da9e6682a0c7e7f1f3195f350c51e14164ce4e170eaaa
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