Instructions to use asnelt/mnistvit-transformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use asnelt/mnistvit-transformers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="asnelt/mnistvit-transformers", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("asnelt/mnistvit-transformers", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 221 Bytes
66be11f | 1 2 3 4 5 6 7 8 9 10 | {
"auto_map": {
"AutoImageProcessor": "image_processing_mnistvit.MnistViTImageProcessor"
},
"image_processor_type": "MnistViTImageProcessor",
"size": 28,
"normalization": "image",
"do_auto_invert": true
}
|