| --- |
| license: cc-by-nc-sa-4.0 |
| tags: |
| - relational-deep-learning |
| - relational-databases |
| - tabular |
| - tabular-classification |
| - tabular-regression |
| - foundation-model |
| - in-context-learning |
| - few-shot |
| - relbench |
| - relational-transformer |
| datasets: |
| - stanford-star/the-join |
| - stanford-star/relbench |
| pipeline_tag: tabular-classification |
| --- |
| |
| # RT-P (`rt-p`) |
|
|
| RT-P 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`](https://huggingface.co/stanford-star/rt-j) |
| — drop-in replacement. |
|
|
| | Variant | Folder | Task | |
| |---|---|---| |
| | Classifier | `classification/` | binary entity classification | |
| | Regressor | `regression/` | 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 |
| |
| ```python |
| from rt.model import RelationalTransformer |
| |
| model = RelationalTransformer.from_pretrained("stanford-star/rt-p/classification") |
| # or: RelationalTransformer.from_pretrained("stanford-star/rt-p", subfolder="regression") |
| ``` |
| |
| ```bash |
| pixi run eval --model.load-ckpt-path stanford-star/rt-p/classification ... |
| ``` |
| |
| ## Related |
| |
| - Training data: [stanford-star/the-join](https://huggingface.co/datasets/stanford-star/the-join) |
| - Evaluation: [RelBench](https://huggingface.co/datasets/stanford-star/relbench) |
| - Reference model: [stanford-star/rt-j](https://huggingface.co/stanford-star/rt-j) |
| |
