Instructions to use mezattn/eva02_base_patch14_448_moderation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mezattn/eva02_base_patch14_448_moderation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mezattn/eva02_base_patch14_448_moderation") 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("mezattn/eva02_base_patch14_448_moderation") model = AutoModelForImageClassification.from_pretrained("mezattn/eva02_base_patch14_448_moderation") - Notebooks
- Google Colab
- Kaggle
| license: mit | |
| base_model: | |
| - timm/eva02_base_patch14_448.mim_in22k_ft_in22k_in1k | |
| pipeline_tag: image-classification | |
| tags: | |
| - pytorch | |
| - transformers | |