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
| license: mit | |
| datasets: | |
| - uoft-cs/cifar10 | |
| - uoft-cs/cifar100 | |
| language: | |
| - en | |
| pipeline_tag: image-classification | |
| library_name: transformers | |
| tags: | |
| - torch | |
| - HVitModel | |