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 training_args.bin from Abhiram4/AnimeCharacterClassifierMark1: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/Abhiram4/AnimeCharacterClassifierMark1/resolve/main/training_args.bin
- Command line
-
hf download hf://Abhiram4/AnimeCharacterClassifierMark1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Abhiram4/AnimeCharacterClassifierMark1/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- 1d33797e9b2c97e633c337c9b31e6d0cb49f9835886347059d34a36b6627980c
- Size of remote file:
- 4.09 kB
- SHA256:
- e8fa55737e8bb0b4efa457eeb13e7da2c5eff67a00649f7db78354c40e5d0c9a
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