Image Classification
Transformers
Safetensors
softmasked_selective_vit
vision-transformer
efficient-transformer
selective-attention
knowledge-distillation
computer-vision
custom_code
Instructions to use XAFT/SM-Selective-ViT-Base-224-Distilled with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use XAFT/SM-Selective-ViT-Base-224-Distilled with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="XAFT/SM-Selective-ViT-Base-224-Distilled", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("XAFT/SM-Selective-ViT-Base-224-Distilled", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download __init__.py from XAFT/SM-Selective-ViT-Base-224-Distilled: direct link, hf CLI and curl.
- Browser
- Download file 220 Bytes
-
https://huggingface.co/XAFT/SM-Selective-ViT-Base-224-Distilled/resolve/ddcb7ea806ccdd94e9715dad1fc503d2c5797f3c/__init__.py
- Command line
-
hf download hf://XAFT/SM-Selective-ViT-Base-224-Distilled@ddcb7ea806ccdd94e9715dad1fc503d2c5797f3c/__init__.py
-
curl -L -o __init__.py https://huggingface.co/XAFT/SM-Selective-ViT-Base-224-Distilled/resolve/ddcb7ea806ccdd94e9715dad1fc503d2c5797f3c/__init__.py
220 Bytes
| from .configuration_selectivevit import SMSelectiveViTConfig | |
| from .modeling_selectivevit import SMSelectiveViTModelForClassification | |
| __all__ = [ | |
| "SMSelectiveViTConfig", | |
| "SMSelectiveViTModelForClassification", | |
| ] | |