--- license: mit tags: - knowledge-graph - hypergraph - legal-evidence - graph-neural-network - unicosys language: - en library_name: transformers pipeline_tag: graph-ml --- # Unicosys Hypergraph Knowledge Model A trainable knowledge graph embedding model encoding the unified evidence hypergraph for Case 2025-137857. ## Model Description This model encodes a **unified hypergraph** linking financial transactions, email communications, legal evidence, and entity relationships into a single trainable knowledge representation. ### Architecture | Component | Details | |---|---| | Node Embedding | 128-dim structural + 256-dim text | | Hidden Dimension | 256 | | Text Encoder | 2-layer Transformer, 4 heads | | Graph Attention | 2-layer GAT, 4 heads | | Link Predictor | 2-layer MLP with margin ranking loss | | Total Parameters | **36,023,681** | ### Knowledge Graph Statistics | Metric | Count | |---|---| | Total Nodes | 272,683 | | Total Edges | 14,816 | | Cross-Links | 3,976 | | Entities | 16 | | Emails | 199,553 | | Financial Documents | 17,036 | | Timeline Events | 54,346 | | LEX Schemes | 13 | | Legal Filings | 7 | ### Subsystems | Subsystem | Nodes | |---|---| | Core (Entities) | 16 | | Fincosys (Financial) | 72,935 | | Comcosys (Communications) | 199,553 | | RevStream1 (Evidence) | 146 | | Ad-Res-J7 (Legal) | 33 | ## Training The model can be fine-tuned on link prediction tasks: ```python from model.unicosys_model import UnicosysHypergraphModel, UnicosysConfig model = UnicosysHypergraphModel.from_pretrained("hyperholmes/unicosys-hypergraph") # ... prepare training data ... # model.forward(node_ids, node_type_ids, subsystem_ids, edge_index, edge_type_ids, # pos_edge_index=pos, neg_edge_index=neg, labels=labels) ``` ## Files - `model.safetensors` — Model weights - `config.json` — Model configuration - `graph_data.safetensors` — Encoded graph tensors (nodes, edges) - `tokenizer.json` — Character-level tokenizer for node labels - `node_id_mapping.json` — Node ID string to integer index mapping - `model_summary.json` — Compact statistics summary ## Source Generated by the [Unicosys](https://github.com/hyperholmes/unicosys) intelligence pipeline.