Contamination MapVision / Model
SigLIP
- Organisation
- Google DeepMind
- Family
- SigLIP
- Released
- 2023-03-27 (arXiv v1 submission date (https://arxiv.org/abs/2303.15343v1))
- Checkpoints
- google/siglip-base-patch16-224, google/siglip-so400m-patch14-384
- Weights
- Open · Apache-2.0
- Links
- PaperModel cardCode
Training data disclosure: Partial list
Level determined for 25% of benchmark cells.
- TestTest data seen0
- SeenSeen, split unclear0
- TrainTraining data seen0
- Related data seen0
- NoNot seen2
- ?Unknown6
“SigLIP is pre-trained on the WebLI dataset”
Training corpora
-
WebLI (Web Language-Image)
· 1 source · pre-training
Evidence that SigLIP uses it
“We pre-train SigLIP models on the WebLI dataset [13], using only English image and text pairs.”
arxiv.org · paper · Section 4.2 · retrieved 2026-10-15 Contents of this corpus
-
images and texts from the public web (alt-text, page title, OCR) (broad web data: may contain benchmark test sets) · split: unknown
Collection-level entry. The crawl is not public and the source pages are not documented.
Evidence
“we introduce WebLI, a multilingual imagelanguage dataset built from images and texts available on the public web.”
arxiv.org · paper · Section 3.2 · retrieved 2026-10-15 “The WebLI dataset covers about 10 billion images and 12 billion alt-texts in 109 languages.”
arxiv.org · paper · Appendix B · retrieved 2026-10-15 “The dataset is built from a subset of public web pages.”
arxiv.org · paper · Appendix G, WebLI datasheet · retrieved 2026-10-15
-
images and texts from the public web (alt-text, page title, OCR) (broad web data: may contain benchmark test sets) · split: unknown
Benchmark cells
Industrial anomaly detection
Unknown MVTec AD · training data not disclosed in enough detail
Not seen MVTec AD 2 · its test items were published from 2025-03-27, after the model's stated training-data cutoff (2022-12-31)
Evidence (3)
“Over what timeframe was the data collected? 2021-2022”
“arXiv:2503.21622v1 [cs.CV] 27 Mar 2025”
“All image data is available at https://www.mvtec.com/company/research/datasets/mvtec-ad-2.”
Unknown MVTec LOCO AD · training data not disclosed in enough detail
Unknown VisA · training data not disclosed in enough detail
Not seen Real-IAD · its test items were published from 2024-03-19, after the model's stated training-data cutoff (2022-12-31)
Unknown MPDD · training data not disclosed in enough detail
Unknown BTAD · training data not disclosed in enough detail
Unknown KolektorSDD2 · training data not disclosed in enough detail
Notes
disclosure is partial_list because WebLI is private and only described in general terms. The WebLI deduplication against 68 datasets is documented in PaLI, not in SigLIP. The checkpoint list is not complete; other sizes and resolutions and a multilingual variant exist on HF.
Sources
- Sigmoid Loss for Language Image Pre-Training · paper · retrieved 2026-10-15
- google/siglip-so400m-patch14-384 model card · model card · retrieved 2026-10-15