Instructions to use tommilyjones/vit-base-patch16-224-finetuned-hateful-meme-restructured-balanced with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tommilyjones/vit-base-patch16-224-finetuned-hateful-meme-restructured-balanced with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="tommilyjones/vit-base-patch16-224-finetuned-hateful-meme-restructured-balanced") 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("tommilyjones/vit-base-patch16-224-finetuned-hateful-meme-restructured-balanced") model = AutoModelForImageClassification.from_pretrained("tommilyjones/vit-base-patch16-224-finetuned-hateful-meme-restructured-balanced", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1 opened almost 2 years ago
by
SFconvertbot