Image Classification
Transformers.js
ONNX
timm
Transformers
vit
detection
deepfake
forensics
deepfake_detection
community
opensight
Instructions to use onnx-community/CommunityForensics-DeepfakeDet-ViT-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use onnx-community/CommunityForensics-DeepfakeDet-ViT-ONNX with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('image-classification', 'onnx-community/CommunityForensics-DeepfakeDet-ViT-ONNX'); - timm
How to use onnx-community/CommunityForensics-DeepfakeDet-ViT-ONNX with timm:
import timm model = timm.create_model("hf_hub:onnx-community/CommunityForensics-DeepfakeDet-ViT-ONNX", pretrained=True) - Transformers
How to use onnx-community/CommunityForensics-DeepfakeDet-ViT-ONNX with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="onnx-community/CommunityForensics-DeepfakeDet-ViT-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/CommunityForensics-DeepfakeDet-ViT-ONNX") model = AutoModelForImageClassification.from_pretrained("onnx-community/CommunityForensics-DeepfakeDet-ViT-ONNX") - Notebooks
- Google Colab
- Kaggle
| { | |
| "crop_pct": 0.875, | |
| "crop_size": 384, | |
| "do_convert_rgb": null, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_processor_type": "ViTImageProcessor", | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 440, | |
| "width": 440 | |
| } | |
| } | |