Instructions to use AdamCodd/vit-base-nsfw-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use AdamCodd/vit-base-nsfw-detector with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('image-classification', 'AdamCodd/vit-base-nsfw-detector'); - Transformers
How to use AdamCodd/vit-base-nsfw-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="AdamCodd/vit-base-nsfw-detector") 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("AdamCodd/vit-base-nsfw-detector") model = AutoModelForImageClassification.from_pretrained("AdamCodd/vit-base-nsfw-detector") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ff06c00704620c336869b8885657a737359b2cedfeeadd02bab6b6fe7d5cf6d
- Size of remote file:
- 50.3 MB
- SHA256:
- 8402aaf2e181980706e1e264727ca9c3b65cc96bd715d6969e75da4010f8b734
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