Contamination MapVision / Model
OpenCLIP (LAION-400M checkpoints)
- Organisation
- LAION / OpenCLIP (mlfoundations)
- Family
- OpenCLIP · version v0.2-weights
- Released
- 2022-04-01 (GitHub release 'v0.2-weights' published_at (GitHub API, https://github.com/mlfoundations/open_clip/releases/tag/v0.2-weights). Earlier LAION-400M weights may have been public before this release.)
- Checkpoints
- ViT-B-32 laion400m_e31, ViT-B-32 laion400m_e32, ViT-B-16 laion400m_e31, ViT-B-16 laion400m_e32, ViT-B-16-plus-240 laion400m_e31, ViT-B-16-plus-240 laion400m_e32, ViT-L-14 laion400m_e31, ViT-L-14 laion400m_e32
- Weights
- Open · MIT
- Links
- PaperCode
Training data disclosure: Full list
Level determined for 50% of benchmark cells.
- TestTest data seen0
- SeenSeen, split unclear0
- TrainTraining data seen0
- Related data seen0
- NoNot seen4
- ?Unknown4
“We ran experiments in an attempt to reproduce OpenAI's ViT results with the comparably sized (and open) LAION-400M dataset.”
Training corpora
-
LAION-400M
· 1 source (complete list) · pre-training
· homepage
Evidence that OpenCLIP (LAION-400M checkpoints) uses it
“The B/16+ 240x240 LAION400M training reached a top-1 ImageNet-1k zero-shot validation score of 69.21.”
raw.githubusercontent.com · readme · LAION-400M, ViT-B/16+ 240x240 · retrieved 2026-10-15 “laion400m_e32=_pcfg(”
raw.githubusercontent.com · code · pretrained.py (ViT-B-32, ViT-B-16, ViT-B-16-plus-240, ViT-L-14) · retrieved 2026-10-15 Contents of this corpus
-
Common Crawl (WAT files, HTML IMG tags with alt-text) (broad web data: may contain benchmark test sets) · split: unknown
Collection-level entry: arbitrary public web images that passed a CLIP-similarity filter.
Evidence
“To create image-text pairs, we parse through WAT files from Common Crawl and parse out all HTML IMG tags containing an alt-text attribute.”
arxiv.org · paper · Section 2.1 · retrieved 2026-10-15 “Then we compute the cosine similarity of both embeddings and drop all samples with cosine similarity below 0.3.”
arxiv.org · paper · Section 2.1.1 · retrieved 2026-10-15
-
Common Crawl (WAT files, HTML IMG tags with alt-text) (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 (2021-12-31)
Evidence (3)
“The image-text-pairs have been extracted from the Common Crawl web data dump and are from random web pages crawled between 2014 and 2021.”
“arXiv:2503.21622v1 [cs.CV] 27 Mar 2025”
“All image data is available at https://www.mvtec.com/company/research/datasets/mvtec-ad-2.”
Not seen MVTec LOCO AD · its test items were published from 2022-02-22, after the model's stated training-data cutoff (2021-12-31)
Evidence (2)
“The image-text-pairs have been extracted from the Common Crawl web data dump and are from random web pages crawled between 2014 and 2021.”
“Published: 22 February 2022”
Not seen VisA · its test items were published from 2022-07-28, after the model's stated training-data cutoff (2021-12-31)
Evidence (3)
“The image-text-pairs have been extracted from the Common Crawl web data dump and are from random web pages crawled between 2014 and 2021.”
“arXiv:2207.14315v1 [cs.CV] 28 Jul 2022”
“We release the Visual Anomaly (VisA) Dataset consisting of 10,821 high-resolution color images (9,621 normal and 1,200 anomalous samples) covering 12 objects in 3 domains”
Not seen Real-IAD · its test items were published from 2024-03-19, after the model's stated training-data cutoff (2021-12-31)
Evidence (2)
“The image-text-pairs have been extracted from the Common Crawl web data dump and are from random web pages crawled between 2014 and 2021.”
“arXiv:2403.12580v1 [cs.CV] 19 Mar 2024”
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
NEW backbone id, not in the shared list. A separate entry is needed because these checkpoints were trained on different data from the LAION-2B ones. For example, ViT-B-16-plus-240 laion400m_e31/e32 is the backbone WinCLIP-style methods commonly use, but those methods' own papers are needed to confirm which tag each uses.
Sources
- OpenCLIP docs/PRETRAINED.md · readme · retrieved 2026-10-15
- OpenCLIP pretrained.py · code · retrieved 2026-10-15