Instructions to use dsaint31/bb_mlp_224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dsaint31/bb_mlp_224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dsaint31/bb_mlp_224") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dsaint31/bb_mlp_224", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download models/microsoft__swin-tiny-patch4-window7-224/preprocessor_config.json from dsaint31/bb_mlp_224: direct link, hf CLI and curl.
- Browser
- Download file 268 Bytes
-
https://huggingface.co/dsaint31/bb_mlp_224/resolve/main/models/microsoft__swin-tiny-patch4-window7-224/preprocessor_config.json
- Command line
-
hf download hf://dsaint31/bb_mlp_224/models/microsoft__swin-tiny-patch4-window7-224/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/dsaint31/bb_mlp_224/resolve/main/models/microsoft__swin-tiny-patch4-window7-224/preprocessor_config.json
268 Bytes
| { | |
| "auto_map": { | |
| "AutoImageProcessor": "ds_proc.BackboneMLPHead224ImageProcessor" | |
| }, | |
| "backbone_name_or_path": "microsoft/swin-tiny-patch4-window7-224", | |
| "image_processor_type": "BackboneMLPHead224ImageProcessor", | |
| "is_training": false, | |
| "use_fast": true | |
| } | |