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rt-plurel
stanford-star/rt-plurel
rt-plurel is a tabular classification model from stanford-star. Use it for the tabular classification task on the model card, and read the license before you ship it in a product. It is set up for pytorch. The card lists the license as cc-by-nc-sa-4.0.
RT-PluRel is a Relational Transformer checkpoint pair for in-context / few-shot entity prediction over multi-table relational databases (no per-task gradient training). Same architecture and file layout as stanford-st…
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.pt1.7 GB · 91%
At a glance
- Task
- Tabular Classification
- Library
- pytorch
- License
- cc-by-nc-sa-4.0
- Access
- Public
- Created
- Feb 3, 2026
- Updated
- Sep 11, 2026
- SHA
- d27c97b0
Model card
From the Hugging Face model README
RT-PluRel (rt-plurel)
RT-PluRel is a Relational Transformer checkpoint pair for in-context /
few-shot entity prediction over multi-table relational databases (no per-task
gradient training). Same architecture and file layout as
stanford-star/rt-j — drop-in
replacement.
Repository layout note (2026-08). This repository now hosts two generations of RT-PluRel checkpoints. The current checkpoint pair (formerly published as
stanford-star/rt-p, which this repository replaces) lives at the repository root, described below. The original checkpoints of the PluRel paper (arXiv:2602.04029), previously at this repository's root, are preserved unchanged underpaper/— seepaper/README.md.
| Variant | Folder | Task |
|---|---|---|
| RT-PluRel | model.safetensors | binary entity classification and entity regression |
Architecture: ~85.6M params · bfloat16 · 12 blocks, d_model 512, 8 heads, d_ff 2048 ·
text columns embedded with all-MiniLM-L12-v2 (d_text 384).
Each folder contains model.safetensors (weights) and config.json
(dims + text-embedding model).
Usage
from rt.model import RelationalTransformer
model = RelationalTransformer.from_pretrained("stanford-star/rt-plurel")
pixi run eval --model.load-ckpt-path stanford-star/rt-plurel ...
paper/: original PluRel-paper checkpoints
The paper/ subdirectory preserves the earlier RT-PluRel release: .pt
checkpoints (12 blocks, d_model 256, d_ff 1024) pretrained on synthetic
relational databases generated by
PluRel, plus the
continued-pretraining and fine-tuned RelBench leaderboard checkpoints. Details,
protocols, and download snippets: paper/README.md.
Paths from before the reorganization gain a paper/ prefix, e.g.
from huggingface_hub import hf_hub_download
ckpt = hf_hub_download("stanford-star/rt-plurel", "paper/synthetic-pretrain_rdb_1024_size_4b.pt")
License
The root checkpoint (model.safetensors) is released under
CC BY-NC-SA 4.0 (see LICENSE). The files under paper/ retain their original
MIT license.
Related
- Training data: stanford-star/the-join
- Evaluation: RelBench
- Reference model: stanford-star/rt-j
- Papers: Relational Transformer (arXiv:2510.06377) · PluRel (arXiv:2602.04029)
- Task
- Tabular Classification
- Library
- pytorch
- License
- cc-by-nc-sa-4.0
- Created
- Feb 3, 2026
- Updated
- Sep 11, 2026