Instructions to use prithivMLmods/ImageShield-SUPER-90M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/ImageShield-SUPER-90M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/ImageShield-SUPER-90M") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/ImageShield-SUPER-90M") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/ImageShield-SUPER-90M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add ImageShield-Guardrail Datasets
#1
by prithivMLmods - opened
Added the following ImageShield-Guardrail datasets to the project:
prithivMLmods/ImageShield-Guardrail-80KprithivMLmods/ImageShield-Guardrail-Realism-60K
These datasets are intended for training and evaluating image safety, guardrail, and content-classification models, with a dedicated focus on general unsafe-content detection and realism-based image classification.
prithivMLmods changed pull request status to merged