| --- |
| license: other |
| license_name: tokenai-neo-model-license |
| 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 |
|
|
| 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. |
|
|
| ## Model architecture |
|
|
| - Bidirectional Transformer encoder, initialized and trained from scratch. |
| - 41,391,654 trainable parameters (approximately 41.4 million). |
| - 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 records |
|
|
| Training code, configurations, live logs, loss history, checkpoints metadata, |
| evaluation reports, and benchmark history are maintained only in the GitHub |
| source repository: |
|
|
| https://github.com/tokenaii/Neo/tree/main/docs/training |
|
|
| This Hugging Face model repository does not publish the training history or |
| benchmark archive. |
|
|
| ## Tokenizer |
|
|
| Neo uses the standard English `bert-base-uncased` tokenizer and vocabulary, |
| published under `tokenizer/` for repository organization. A custom tokenizer |
| was not built. The Transformer parameters are Neo's own randomly initialized |
| and trained weights; the tokenizer vocabulary is not the model architecture. |
|
|
| ## Release status |
|
|
| The English-only training run is complete and the verified |
| `model.safetensors` checkpoint is published in this repository. Training logs, |
| loss history, evaluation reports, and benchmark records remain exclusively in |
| the GitHub source repository. Do not infer benchmark accuracy from the |
| architecture or data counts. |
|
|
| ## 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. |
| - `model.safetensors` — verified model weights. |
| - `tokenizer/` — standard English `bert-base-uncased` tokenizer files. |
|
|
| ## License and attribution |
|
|
| Use is governed by [the TokenAI Neo Model License](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. |
|
|
