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 +1 -1
- config.json +1 -1
- model.safetensors +1 -1
- preprocessor_config.json +1 -0
- runs/events.out.tfevents.1734760433.3c8577f315f5.549.0 +3 -0
README.md
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metrics:
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- name: Accuracy
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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: 0.8330780863761902
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---
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# sanali209/nsfwfilter
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config.json
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"problem_type": "single_label_classification",
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.
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}
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"problem_type": "single_label_classification",
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.47.1"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 343230128
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version https://git-lfs.github.com/spec/v1
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size 343230128
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preprocessor_config.json
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{
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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{
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"do_convert_rgb": null,
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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runs/events.out.tfevents.1734760433.3c8577f315f5.549.0
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version https://git-lfs.github.com/spec/v1
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size 6703
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