tokenaii
/

Neo

@@ -1,83 +1,133 @@
 ---
 license: other
-license_name: tokenai-neo-dataset-license
-license_link: https://huggingface.co/datasets/tokenaii/Neo-dataset/blob/main/legal/DATASET_LICENSE.md
-language:
-- en
-task_categories:
-- text-classification
 tags:
 - system-one
 - decision-model
 - rlcd
-- synthetic
 - tool-routing
 ---
-# NEO - Decision Model Dataset
-<p align="center"><img src="assets/neo-cover.png" alt="NEO - Decision Model Dataset" width="360"></p>
-TokenAI is a non-profit startup founded in 2025 by Assem Sabry, based in Alexandria, Egypt. The dataset,
-model, source code, documentation, and related materials are owned by TokenAI.
-Contact: info@tokenai.llc · https://tokenai.llc
-Canonical reference: `tokenaii/Neo` — https://huggingface.co/tokenaii/Neo
-Complete source repository: [github.com/tokenaii/Neo](https://github.com/tokenaii/Neo).
-It contains the complete project source code, training code, synthetic-data
-generation code, evaluation and benchmark scripts, configurations, examples,
-documentation, licenses, and reproducibility materials. This repository
-contains the dataset files, manifest, provenance information, and dataset legal
-notices.
-Synthetic, schema-driven decision records for training and evaluating Neo, a System One decision model.
-## Contents
-- 1,000,000 individual decisions.
-- 400,000 state records.
-- `choice`, `score`, and `noul` questions.
-- English-only state text, questions, labels, and tool descriptions.
-- Tool routing, urgency, human-review, ambiguity, distractor tools, option permutations, and unknowable cases.
-## Provenance
-The records are generated by the `neo-synthetic` generator in the Neo repository. No rows from public datasets are copied into the generated corpus. Public datasets are used only for schema design, sanity checks, or separately documented evaluation.
-Generator: `neo-english-synthetic`.
-Generator seed: `20261003`.
-The complete source file used by training has SHA-256
-`3eff0bcf1ced0e748698fefefcf8069d2cc997888d7568fddb5ccd6a1a651c50`.
-The four files under `data/` are a byte-preserving concatenation of that
-training source.
-## Splits
-- `train`: 799,882 decisions
-- `calibration`: 100,138 decisions
-- `test`: 99,980 decisions
-The calibration split is reserved for probability calibration. The test split must not be used to select checkpoints, thresholds, or temperature.
-## Intended use and limitations
-This dataset is a research corpus for typed decision models. It is not a substitute for domain-specific validation, human review, or safety testing. Synthetic distributions can contain template artifacts and must not be treated as real user behavior.
-## Identity and license
-This dataset must remain identified as the **TokenAI Neo Decision Model Dataset** and must
-retain the canonical reference `tokenaii/Neo`. Rebranding, renaming,
-white-labeling, redistributing, rehosting, or publishing it under another
-identity is prohibited. The dataset must not be used without preserving its
-reference and provenance. See [the dataset license](legal/DATASET_LICENSE.md)
-and [the ownership notice](legal/NOTICE.md).
-Commercial, monetized, paid, sponsored, advertising-supported, production,
-client, resale, or financially beneficial use is forbidden. Any model or
-experiment trained with this dataset must clearly state that it used
-`tokenaii/Neo-dataset`.
-Third-party datasets referenced by the project are not included in this release
-and retain their own terms.

 ---
 license: other
+license_name: tokenai-neo-model-license-v3.0
+license_link: https://huggingface.co/tokenaii/Neo/blob/main/licenses/MODEL_LICENSE.md
+library_name: pytorch
+pipeline_tag: text-classification
 tags:
 - system-one
 - decision-model
 - rlcd
 - tool-routing
+- en
 ---
+# NEO - Decision Model
+<p align="center"><img src="assets/neo-cover.png" alt="NEO - Decision Model" width="360"></p>
+## Ownership and contact
+TokenAI is a non-profit startup founded in 2025 by Assem Sabry, based in
+Alexandria, Egypt. The Neo model, source code, training data, documentation,
+and related materials are owned by TokenAI.
+Contact: **info@tokenai.llc** · https://tokenai.llc
+## Summary
+Neo is a compact TokenAI System One decision model for selecting actions from a
+declared candidate set. It reads English application context and a typed
+decision schema, then returns calibrated outputs for `choice`, `score`, and
+`noul` in one encoder forward pass. It is not a conversational or free-form
+text-generation model.
+Canonical model: `tokenaii/Neo` — https://huggingface.co/tokenaii/Neo
+Training dataset: `tokenaii/Neo-dataset` — https://huggingface.co/datasets/tokenaii/Neo-dataset
+## Model architecture
+- Bidirectional Transformer encoder, initialized and trained from scratch.
+- Approximately 110 million parameters.
+- 8 Transformer layers; hidden size 512; 8 attention heads.
+- Intermediate size 2048; maximum context 1024 tokens.
+- Typed heads: `choice`, `score`, and `noul`.
+- Choice head: up to 32 candidate options per question.
+- Score head: up to 5 ordered levels.
+- Noul head: binary probability for a yes/no or escalation decision.
+- A request can contain up to 8 independent decision questions.
+## Input and output contract
+The input is English text plus a predefined decision schema and candidate
+options. The output contains typed probabilities and the selected index or
+level. Applications should apply their own confidence thresholds, abstention
+rules, validation, logging, and human review. Neo does not execute tools and
+does not replace authorization or policy enforcement.
+## Intended uses
+Non-commercial research and education for tool routing, workflow selection,
+request classification, department routing, escalation detection, validation
+gates, and selecting the next action in an agent pipeline.
+## Out-of-scope uses
+The license prohibits commercial, monetized, paid, sponsored, client-facing,
+production-business, or financially beneficial use. Do not use Neo for
+unsupervised medical, legal, financial, employment, housing, admissions,
+insurance, credit, safety-critical, government-benefit, law-enforcement, or
+irreversible decisions.
+## Training data and procedure
+The English-only corpus contains 400,000 synthetic records and 1,000,000
+independent decisions: 799,882 training, 100,138 calibration, and 99,980 test
+decisions. The catalog contains 20 tools; records commonly present one target
+and five distractors.
+The training run uses RLCD-inspired weighted soft-target training from scratch,
+20 epochs, approximately 15,640 optimizer steps, batch size 1024, bfloat16,
+learning rate `0.0002`, choice loss weight `8.0`, and score/noul weights `1.0`.
+The generator is identified as `neo-english-synthetic-v1` in the project
+manifests. The final benchmark report is produced after training and is not
+claimed by this card until verified.
+## Tokenizer
+Neo uses the standard English `bert-base-uncased` tokenizer and vocabulary. A
+custom tokenizer was not built for this release, so no custom tokenizer is
+claimed or published under `tokenizer/`. The Transformer parameters are Neo's
+own randomly initialized and trained weights; the tokenizer vocabulary is not
+the model architecture.
+## Release status
+The previous model weights were removed from this repository before the final
+English-only training release. The current repository contains documentation,
+configuration, tokenizer metadata, and licenses while the English training and
+automatic evaluation pipeline complete. Do not infer benchmark accuracy from
+the architecture or data counts. Verified results will be published only after
+the local evaluation artifacts are reviewed.
+## Repository layout
+- `licenses/MODEL_LICENSE.md` — full model license.
+- `licenses/NOTICE.md` — attribution and ownership notice.
+- `assets/neo-cover.png` — repository artwork.
+- `docs/MODEL_SPECIFICATION.md` — technical specification.
+- `tokenizer/` — reserved for a custom tokenizer only if one is actually built.
+- `training_config.json` — reproducibility metadata when a release includes it.
+## License and attribution
+Use is governed by [the TokenAI Neo Model License v3.0](licenses/MODEL_LICENSE.md).
+Redistribution, renaming, rebranding, white-labeling, Derivative Models,
+Commercial Use, and Financial Benefit are prohibited without written permission
+from TokenAI. Every permitted downstream report or model must state:
+> This work was trained using the TokenAI Neo Decision Model Dataset:
+> `tokenaii/Neo-dataset`.
+Permission requests must be sent to **info@tokenai.llc**. The complete legal
+terms, trademark policy, notice-and-takedown process, patent reservation,
+contribution/CLA rules, and dependency obligations are in the linked license.
+## Limitations
+Neo is trained on synthetic English decision records and may fail on unseen
+schemas, ambiguous contexts, distribution shifts, adversarial options, or
+languages other than English. Calibration and accuracy are task-dependent.
+Always validate with held-out, task-specific data and add human oversight for
+high-impact workflows.