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
commit files to HF hub
Browse files
README.md
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metrics:
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type: accuracy
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value: 0.
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---
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# sanali209/nsfwfilter
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.8785594701766968
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---
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# sanali209/nsfwfilter
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model.safetensors
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runs/events.out.tfevents.1732327883.db70281c3d0d.3987.0
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