Image Classification
timm
PyTorch
Safetensors
Transformers
variance_pad_eva
feature-extraction
custom_code
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("bn22/vit_medium_patch28_rope_reg4_gap_224", trust_remote_code=True, dtype="auto")Quick Links
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="bn22/vit_medium_patch28_rope_reg4_gap_224", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")