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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sanali209/nsfwfilter: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/sanali209/nsfwfilter/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sanali209/nsfwfilter/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sanali209/nsfwfilter/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 0006ea886da28c4b335f454ba02eb424b8879206a7119e4436cffec88739d2c9
- Size of remote file:
- 343 MB
- SHA256:
- 67b923b85581f8809c8e3f98d6113f06414d84eb6a5e515a4b159367e36b7d01
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