Microsoft
The Table Transformer is equivalent to DETR, a Transformer-based object detection model. Note that the authors decided to use the "normalize before" setting of DETR, which means that layernorm is applied before self- and cross-attention.
Running this yourself: can likely run on your own machine.
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29.7
Quality Score
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Arena ELO
29M
Parameters
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Context
This measures the amount of verifiable public evidence we have, not how capable the model is. A missing field means it has not been verified yet, not that its value is zero.
15 of 22 public signals
Use this section to answer one simple question first: how much outside evidence do we have that this model performs well? Structured benchmark scores appear first, then official provider evidence, then live arena signal.
This model has official provider benchmark evidence, but not a normalized independent benchmark table yet.
A full normalized benchmark row is not available for this model yet.
Official benchmark evidence is already available below, so this release is still being tracked while the normalized table catches up.
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1.1M
Downloads
230
Likes
Oct 2022
Released
4/5 signals
2/4 signals
3/5 signals
3/4 signals
3/4 signals
Parameters
29M
Training compute
Not reported
Dataset scale
Not reported
Base model
Not reported
Gaps we are still tracking
Metadata sources
These are recent benchmark or leaderboard claims from official provider sources. They are useful for freshness and context, but they are not treated the same as normalized independent benchmark rows.
MAI-Image keeps climbing! Now #3 on @arena's image editing leaderboard. Our latest MAI-Image model is available in Private Preview on Microsoft Foundry. https://t.co/ib8IBXNbXA
MAI-Image keeps climbing! Now #3 on @arena's image editing leaderboard. Our latest MAI-Image model is available in Private Preview on Microsoft Foundry. https://t.co/ib8IBXNbXA
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