Instructions to use creative-graphic-design/MVANet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use creative-graphic-design/MVANet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="creative-graphic-design/MVANet", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("creative-graphic-design/MVANet", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 373 Bytes
28c79f5 f685c19 28c79f5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"auto_map": {
"AutoImageProcessor": "image_processing_mvanet.MVANetImageProcessor"
},
"do_normalize": true,
"do_resize": true,
"image_mean": [
0.485,
0.456,
0.406
],
"image_processor_type": "MVANetImageProcessor",
"image_std": [
0.229,
0.224,
0.225
],
"resample": 2,
"size": {
"height": 1024,
"width": 1024
}
}
|