Data · dataset · 2026
Berna R7 v0.1.0 — Documentation and Code for a 1.06B Multilingual Language Model with Modular Cell-Based Architecture
Listed in Teesside University Research Data Repository
Berna R7 is a 1.06B-parameter multilingual language model trained from scratch on English, Mathematics, and Code (2.66B tokens).
Description
It is the first implementation of the DNA-Kernel Plexus architecture proposed in Berna R5 (DOI: 10.5281/zenodo.23015308). This dataset (v0.1.0) contains: - Architecture documentation (ARCHITECTURE.md, DNA.md) - Cell lifecycle implementation: saturation (6D knowledge vector), DNA Kernel (100 chromosomes x 4 genes), splitting mechanism (S >= S*), dynamic plexus graph - Training pipeline: train.py, dataset.py, eval.py - Experiment scripts for H1 (saturation-triggered splitting) and H2 (bounded forgetting) - Baselines: vanilla transformer, EWC, PackNet - SQL registry with schema for model lineage and connection tokens - Paper outline - Bundled documentation PDF Status: Model weights are still training; they will be released as v0.2.0.
Key facts: - Parameters: 1,056,265,728 (1.06B) - Data: 2.66B tokens - Hardware: 1x RTX 5090 (32 GB) - License: Berna Research License v1.0 Related works: - Berna R5: DOI 10.5281/zenodo.23015308 - Zenodo mirror: DOI 10.5281/zenodo.23037065 - GitHub: github.com/Berna-Labs/berna-r7 - HuggingFace: huggingface.co/BernaLabs/berna-r7-mother
Links
Where it is published
- DOI doi.org/10.17632/k24wwx6tp6.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
Provenance · 1 source records, 12 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/k24wwx6tp6.1 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4602 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Artificial Intelligence'] |
| concepts[field].anzsrc:group:4611 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Machine Learning'] |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license_text | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |