dleemiller / siglip2-math-base-patch16-256

huggingface.co
Total runs: 12
24-hour runs: 0
7-day runs: 1
30-day runs: 6
Model's Last Updated: November 07 2025
zero-shot-image-classification

Introduction of siglip2-math-base-patch16-256

Model Details of siglip2-math-base-patch16-256

SigLip2 Math

This version of siglip2 is fine tuned on shiwk24/MathCanvas-Imagen using the code_derived_captions split. I trained for 1 epoch on 4M math images, with a random selection between the tikz code or caption using a batch size of 640.

This is not a classification model, since the loss function was pairwise contrastive loss. Use for embedding or downstream classifier training is recommended.

image

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12
Total runs
0
24-hour runs
1
3-day runs
1
7-day runs
6
30-day runs

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siglip2-math-base-patch16-256 is an open source model from GitHub that offers a free installation service, and any user can find siglip2-math-base-patch16-256 on GitHub to install. At the same time, huggingface.co provides the effect of siglip2-math-base-patch16-256 install, users can directly use siglip2-math-base-patch16-256 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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dleemiller
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Total runs: 20
Run Growth: -46
Growth Rate: -230.00%
Updated:March 06 2025