Image Classification
Transformers
Safetensors
English
siglip
Content Safety
Mature
Content
Detection
Enticing
Sensual
Neutral
Anime
ViT
multi-label
digital spaces
SigLIP2
vision-language encoder
single-label
2e-4
Instructions to use prithivMLmods/Mature-Content-Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Mature-Content-Detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Mature-Content-Detection") 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/Mature-Content-Detection") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Mature-Content-Detection") - Inference
- Notebooks
- Google Colab
- Kaggle
CPU
#1
by MrDevolver - opened
Hello, would this work on CPU fast enough to process big batches of images? I'm looking for a non-GPU solution to process big batches of images in a reasonable time. Has anyone tested this on CPU? If so, how fast it really is?