Image Classification
Transformers
Safetensors
English
metaclip_2
text-generation-inference
Content-filtering
Eval Results (legacy)
Not-For-All-Audiences
Instructions to use prithivMLmods/Nsfw_Image_Detection_OSS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Nsfw_Image_Detection_OSS with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Nsfw_Image_Detection_OSS") 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/Nsfw_Image_Detection_OSS") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Nsfw_Image_Detection_OSS", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aef37d23f33db6e4243952a8ddae090484e2ec41ee1589984fcce796096455da
- Size of remote file:
- 5.2 kB
- SHA256:
- cddbaf8fc28bf5b8af4e972e6227e3b18cd5d54090fc40ee776e5477e89bce37
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.