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")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Mature-Content-Detection") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Mature-Content-Detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from prithivMLmods/Mature-Content-Detection: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/prithivMLmods/Mature-Content-Detection/resolve/main/training_args.bin
- Command line
-
hf download hf://prithivMLmods/Mature-Content-Detection/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/prithivMLmods/Mature-Content-Detection/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- a01f68ba72a3331576d00653dddd90f8768503ddaf105fb96f4f22e0802c1a39
- Size of remote file:
- 5.3 kB
- SHA256:
- 77f0ca87b3994c04b4f018469a0d2842d64d1c9897f79e494161c2d4afdb6510
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