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", dtype="auto") - Notebooks
- Google Colab
- Kaggle
metadata
license: mit
datasets:
- uoft-cs/cifar10
- uoft-cs/cifar100
language:
- en
pipeline_tag: image-classification
library_name: transformers
tags:
- torch
- HVitModel