Designsystem Set Membership Siglip2 Demo
This repository contains the trained checkpoint and local config/processor files used by the Design System set-membership web demo.
Fuente del modelo
- Tipo
- Other
- Tamaño del archivo
- 1,44 GB
- Versión
- vRevision a995fee
- Actualizado
- 13 oct 2026
- Descargas
- 0
- Fuente
- Hugging Face
Descripción de la fuente
Design System Set-Membership SigLIP2 Demo Checkpoint
This repository contains the trained checkpoint and local config/processor files used by the Design System set-membership web demo.
Files
checkpoint.pt: PyTorch checkpoint for the set-membership discriminator.hf/google--siglip2-base-patch16-224/: local Hugging Face config/processor files forgoogle/siglip2-base-patch16-224.
The demo app instantiates the SigLIP2 architecture from config and then loads the trained checkpoint weights from checkpoint.pt.
Checkpoint Provenance
Source path on Gautschi:
/scratch/gautschi/jasonwu/designsystem/design_discriminator_runs/setmem-default-additive-x-res-bce-pat4000-20260630T053443Z/checkpoint.pt
SHA-256:
8eeb0b943e7bbb8cb30dcf2ca2302b3ab50bc853c67e4f35165fd26bbfc87092
Training args subset:
model_name = google/siglip2-base-patch16-224
compatibility_mode = additive_x_residual
set_encoder = transformer
set_hidden_dim = 512
direct_scorer_layers = 2
preprocess_crop_top = 0.1
preprocess_crop_bottom = 0.1
preprocess_target_short_side = 256
Intended Use
This checkpoint is intended for the companion Flask web demo package. It scores whether a candidate screenshot belongs to the same design system as uploaded context screenshots.
Uploaded images should be preprocessed before SigLIP encoding with the checkpoint training settings: crop 10% top, crop 10% bottom, resize short side to 256.
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Extractos de fuentes
2 extractos--- license: apache-2.0 library_name: transformers tags: - siglip - image-classification - design-systems - set-membership --- # Design System Set-Membership SigLIP2 Demo Checkpoint This repository contains the trained checkpoint and local config/processor files used by the Design System set-membership web demo. ## Files - `checkpoint.pt`: PyTorch checkpoint for the set-membership discriminator. - `hf/google--siglip2-base-patch16-224/`: local Hugging Face config/processor files for `google/siglip2-base-patch16-224`. The demo app instantiates the SigLIP2 architecture from config and then loads the trained checkpoint weights from `checkpoint.pt`. ## Checkpoint Provenance Source path on Gautschi: ```text /scratch/gautschi/jasonwu/designsystem/design_discriminator_runs/setmem-default-additive-x-res-bce-pat4000-20260630T053443Z/checkpoint.pt ``` SHA-256: ```text 8eeb0b943e7bbb8cb30dcf2ca2302b3ab50bc853c67e4f35165fd26bbfc87092 ``` Training args subset: ```text model_name = google/siglip2-base-patch16-224 compatibility_mode = additive_x_residual set_encoder = transformer set_hidden_dim = 512 direct_scorer_layers = 2 preprocess_crop_top = 0.1 preprocess_crop_bottom = 0.1 preprocess_target_short_side = 256 ``` ## Intended Use This checkpoint is intended for the companion Flask web demo package. It scores whether a candidate screenshot belongs to the same design system as uploaded context screenshots. Uploaded images should be preprocessed before SigLIP encoding with the checkpoint training settings: crop 10% top, crop 10% bottom, resize short side to 256.
Source context: 0 downloads · 0 likes · Pipeline image-classification · Library transformers · Repo ciderlab/designsystem-set-membership-siglip2-demo
