Instructions to use BiliSakura/EUPE-ViT-T with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BiliSakura/EUPE-ViT-T with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="BiliSakura/EUPE-ViT-T")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BiliSakura/EUPE-ViT-T", dtype="auto") - EUPE
How to use BiliSakura/EUPE-ViT-T with EUPE:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
| { | |
| "do_resize": true, | |
| "size": { | |
| "height": 256, | |
| "width": 256 | |
| }, | |
| "resample": 2, | |
| "do_rescale": true, | |
| "rescale_factor": 0.00392156862745098, | |
| "do_normalize": true, | |
| "image_mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "image_std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "do_convert_rgb": true, | |
| "data_format": "channels_first", | |
| "image_processor_type": "BaseImageProcessor" | |
| } | |