Image Classification
Transformers.js
ONNX
PyTorch
Transformers
vit
ViT
real-fake-detection
deep-fake
ai-detect
ai-image-detection
Eval Results (legacy)
Instructions to use onnx-community/ai-image-detect-distilled-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use onnx-community/ai-image-detect-distilled-ONNX with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('image-classification', 'onnx-community/ai-image-detect-distilled-ONNX'); - Transformers
How to use onnx-community/ai-image-detect-distilled-ONNX with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="onnx-community/ai-image-detect-distilled-ONNX") 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("onnx-community/ai-image-detect-distilled-ONNX") model = AutoModelForImageClassification.from_pretrained("onnx-community/ai-image-detect-distilled-ONNX", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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