Instructions to use tommilyjones/vit-base-patch16-224-finetuned-hateful-meme-restructured 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 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") 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("tommilyjones/vit-base-patch16-224-finetuned-hateful-meme-restructured") model = AutoModelForImageClassification.from_pretrained("tommilyjones/vit-base-patch16-224-finetuned-hateful-meme-restructured", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 189 Bytes
78ce630 | 1 2 3 4 5 6 7 8 | {
"epoch": 9.92,
"eval_accuracy": 0.552,
"eval_loss": 0.7151782512664795,
"eval_runtime": 6.2797,
"eval_samples_per_second": 79.621,
"eval_steps_per_second": 2.548
} |