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Sigmoid Loss Optimization

# Sigmoid Loss Optimization

Vit Large Patch16 Siglip 256.v2 Webli
Apache-2.0
Vision Transformer model based on SigLIP 2 architecture, designed for image feature extraction, trained on the webli dataset
Image Classification Transformers
V
timm
525
0
Vit Base Patch16 Siglip 224.v2 Webli
Apache-2.0
ViT model based on SigLIP 2, focused on image feature extraction, trained on the webli dataset
Text-to-Image Transformers
V
timm
1,992
0
Vit Gopt 16 SigLIP2 256
Apache-2.0
SigLIP 2 vision-language model trained on WebLI dataset, suitable for zero-shot image classification tasks.
Text-to-Image
V
timm
43.20k
0
Vit B 16 SigLIP2
Apache-2.0
A SigLIP 2 vision-language model trained on the WebLI dataset, suitable for zero-shot image classification tasks.
Text-to-Image
V
timm
11.26k
0
Vit SO400M 14 SigLIP 384
Apache-2.0
SigLIP (Sigmoid Loss for Language-Image Pretraining) model trained on the WebLI dataset, suitable for zero-shot image classification tasks.
Text-to-Image
V
timm
158.84k
79
Vit L 16 SigLIP 384
Apache-2.0
SigLIP (Sigmoid Loss for Language-Image Pre-training) model trained on the WebLI dataset for zero-shot image classification tasks.
Text-to-Image
V
timm
3,008
27
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