# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("timm/vit_base_patch16_siglip_gap_224.webli", device_map="auto")Quick Links
Model card for vit_base_patch16_siglip_gap_224.webli
timm SigLIP (image encoder only, with global avg pooling) weights from https://huggingface.co/timm/ViT-B-16-SigLIP
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/vit_base_patch16_siglip_gap_224.webli")