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AutoModel wrapper for the SigLIP2 feature-to-pixel decoder used in this repository.1import torch
2from transformers import AutoModel
3
4model = AutoModel.from_pretrained(
5 "toilaluan/f2p_decoder",
6 trust_remote_code=True,
7).eval()
8
9features = torch.randn(1, 257, 1152)
10reconstruction = model(features)
11print(reconstruction.shape) # (1, 3, 224, 224)google/siglip2-so400m-patch14-224. The output is an image tensor in the
decoder's reconstructed pixel space..pt checkpoint: nyu-visionx/siglip2_decoder/model.pt.