Instructions to use codewithdark/hvit-transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codewithdark/hvit-transformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="codewithdark/hvit-transformer") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import PretrainHvitTrans model = PretrainHvitTrans.from_pretrained("codewithdark/hvit-transformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 283 Bytes
b8a5a00 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"architectures": [
"PretrainHvitTrans"
],
"backbone": "resnet50",
"dropout": 0.3,
"embed_dim": 512,
"model_type": "hvit-transformer",
"num_classes": 10,
"num_heads": 8,
"torch_dtype": "float32",
"transformer_layers": 2,
"transformers_version": "4.48.3"
}
|