Readers v11: the choice (readers/choice.json) replaces the refusal; cards describe the four readers
d494912 verified | license: apache-2.0 | |
| base_model: | |
| - Qwen/Qwen2.5-0.5B | |
| - FacebookAI/xlm-roberta-base | |
| - FacebookAI/xlm-roberta-large | |
| library_name: peft | |
| tags: | |
| - text-to-sql | |
| - table-question-answering | |
| - schema.org | |
| - lora | |
| # Prereasoner Runtime Weights | |
| This repository contains the public, manifest-pinned runtime weights for | |
| [Prereasoner](https://github.com/ManiDoraisamy/prereasoner-data), an interpretable | |
| table-question-answering system. Learned components produce semantic evidence: named coordinates | |
| for columns and question words, Schema.org property and class scores, and the own-data readers' | |
| readings of a question (which tables, columns, values, groups, orders and calculations it asks for). | |
| A deterministic typed AST builder makes every query from those readings and owns joins, calculation | |
| verification, rendering, and execution. No model in this bundle writes SQL, and the bundle is not a standalone text-to-SQL model. | |
| ## Install | |
| No Hugging Face account or token is required: | |
| ```bash | |
| git clone https://github.com/ManiDoraisamy/prereasoner-data.git | |
| cd prereasoner-data | |
| python -m engine.fetch_weights | |
| ``` | |
| `engine/data/weights_manifest.json` pins this repository at an immutable commit and records the | |
| SHA-256 digest of every required file. The fetcher downloads into a temporary directory, verifies | |
| the complete bundle, and only then installs it. | |
| ## Bundle Contents | |
| | File | Purpose | | |
| |---|---| | |
| | `encoder.pt` | State dictionary for the relational semantic readout | | |
| | `encoder_meta.pt` | Readout allocation and constructor configuration | | |
| | `qwen_lora/adapter_model.safetensors` | LoRA adapter for `Qwen/Qwen2.5-0.5B` | | |
| | `qwen_lora/adapter_config.json` | PEFT adapter configuration | | |
| | `anchor_assignment.npz` | Calibrated named-dimension thresholds | | |
| | `primitives.npz` | Learned primitive-composition head | | |
| | `schema_property_head.pt` | Calibrated Schema.org named-property evidence head | | |
| | `readers/stage1/` | Own-data schema-item model (XLM-R base): scores each table's and column's use | | |
| | `readers/stage2_a/` to `readers/stage2_d/` | Four own-data reading models (XLM-R large); each `reader.json` says whether it reads the question's values beside their columns | | |
| | `readers/rescorer/` | Re-scorer (XLM-R base): scores the readings' queries that ran | | |
| | `readers/choice.json` | The readers' choice: a logistic model over the re-scorer's logit and how many readers build a query, fitted on held-out calibration databases; it ranks the queries and refuses below its threshold | | |
| The source repository contains the small ontology, calibration, taxonomy, and manifest artifacts. | |
| The base Qwen model is downloaded separately from its publisher. The readers' directories hold their | |
| complete fine-tuned weights (encoders in bfloat16, heads in float32) and tokenizer files. `python -m engine.fetch_weights` | |
| downloads only the files the source manifest lists. Prereasoner loads no SQL-generating model; the | |
| retired SQL proposer adapter (`sql_proposer/`) was removed from this repository on 2026-10-02 and | |
| remains in its history. | |
| ## Model Boundary | |
| The encoder adapter emits named Schema.org property probabilities, calibrated class proposals, and | |
| embeddings for column typing and the structural intent of composition and world questions. A released | |
| class may propose a coarse resolver family, but no score can authorize a table, join, calculation, or | |
| answer. Own-data questions are read by separate XLM-R readers (`engine/data/readers/`); a deterministic | |
| builder makes each of their readings a typed query, and no model writes SQL. The optional Gemini model | |
| serves only the chat orchestrator, starter questions and reference generation, and is not part of | |
| this bundle. | |
| Deterministic code applies ontology mapping, exact source grounding, typed constraints, abstention | |
| rules, and execution checks. | |
| Schema.org 30.0 supplies the named semantic coordinate system. Wikidata and publisher datasets | |
| supply observations mapped into those coordinates; mutable source facts are not intended to be | |
| memorized as answers. | |
| ## Evaluation And Provenance | |
| See the source repository's | |
| [model card](https://github.com/ManiDoraisamy/prereasoner-data/blob/main/docs/MODEL_CARD.md), | |
| [data card](https://github.com/ManiDoraisamy/prereasoner-data/blob/main/docs/DATA_CARD.md), and | |
| [Spider results](https://github.com/ManiDoraisamy/prereasoner-data/blob/main/spider/results/RESULTS.md) | |
| for component boundaries, denominators, and limitations. | |
| The bytes in this bundle are immutable and hash-verified. The promoted Schema.org head has a | |
| machine-readable corpus, split, seed, dependency, encoder, and held-out metric manifest. The shared | |
| encoder's historical training run has less completely recorded source-corpus provenance; do not combine metrics from the two | |
| tracks. All 926 Schema.org classes are representable, but only the released calibrated subset is | |
| servable. Unsupported and under-calibrated coordinates abstain. | |
| ## Intended Use | |
| - Semantic evidence for the matching Prereasoner source revision. | |
| - Research on deterministic SQL planning informed by named learned dimensions. | |
| - Local table and spreadsheet question answering with inspectable plans. | |
| ## Out Of Scope | |
| - Standalone SQL or answer generation. | |
| - Authoritative identity or entity classification. | |
| - High-stakes medical, legal, tax, financial, or safety decisions without source-specific review. | |
| - Using the files with an unverified or incompatible source revision. | |
| ## License | |
| The Prereasoner weight bundle is released under Apache-2.0. The base model and source datasets retain | |
| their own licenses and terms. The readers in `readers/` are fine-tuned from XLM-RoBERTa (MIT) on Spider's | |
| train and dev questions (Yu et al., EMNLP 2018; CC BY-SA 4.0), BIRD train (Li et al., NeurIPS 2023; | |
| CC BY-SA 4.0) and Spider-Syn (Gan et al., ACL 2021; MIT), and on questions Gemini on Vertex AI wrote | |
| over those training databases; keep those attributions when redistributing them. The Spider test set | |
| appears in no training step. The retired `sql_proposer/` adapter in earlier revisions was trained on | |
| Spider TRAIN (Yu et al., EMNLP 2018; CC BY-SA 4.0); keep that attribution when redistributing it. See | |
| [`THIRD_PARTY.md`](https://github.com/ManiDoraisamy/prereasoner-data/blob/main/THIRD_PARTY.md). | |