Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
vit
huggingpics
Eval Results (legacy)
Instructions to use sanali209/nsfwfilter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sanali209/nsfwfilter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sanali209/nsfwfilter") 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("sanali209/nsfwfilter") model = AutoModelForImageClassification.from_pretrained("sanali209/nsfwfilter") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8edefabb43a3062260e89cdae9d46dd729939ae48fd8c4978aa1533cd153c43e
- Size of remote file:
- 7.08 kB
- SHA256:
- cdf2a10e86095f721d8d8343564c1d2cb11b0b4bb9e87b141f37fbaa207e30d5
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