**Model Development at rolodexter** focuses on the design, fine-tuning, evaluation, and deployment of AI models across diverse domains. Our approach is rooted in modular intelligence and agentic abstraction — enabling **multi-agent orchestration**, **context-rich specialization**, and **trust-based deployment**. We support full-stack model development pipelines from raw data ingestion to fine-tuned agent integration. Models can be human-aligned, self-supervised, multi-modal, or embedded within broader knowledge architectures and verification workflows. --- ## Capabilities ### 🧠 Custom Model Design - Foundation model selection - Architectural prototyping (transformers, RNNs, GNNs, etc.) - Prompt-engineered vs instruction-tuned vs RLHF pathways - Modular agent head design for downstream tasking ### 🔁 Model Training & Fine-Tuning - Few-shot / zero-shot learning integration - Domain-specific dataset alignment - Adapter/LoRA layering - Federated learning & differential privacy support ### 🧪 Evaluation & Testing - Bias, toxicity, and robustness testing - Cross-task generalization scoring - Dataset hallucination audits - Agentic unit test generation ### 🔐 Deployment & Governance - Smart contract-wrapped models - Agent policy overlays - Privacy-preserving inference - On-chain model versioning and audits --- ## Use Cases - 🗃️ **Document Intelligence Models** Custom LLMs trained for legal, medical, or regulatory reasoning using structured knowledge graphs and chain-of-thought embeddings. - 🧬 **Scientific Discovery Agents** Models optimized for hypothesis generation, symbolic regression, synthetic chemistry, or metascientific exploration. - 🕸️ **Multi-Agent Systems** Model primitives deployed as cognitive agents within swarm labor meshes, each with bounded utility and verification rules. - 🧾 **Data-to-Insight Pipelines** Fine-tuned agents that convert structured or semi-structured datasets into semantic summaries, dashboards, or forecasts. --- ## Technical Toolchain |Layer|Tools| |---|---| |**Training**|PyTorch, Hugging Face Transformers, LoRA, Deepspeed| |**Fine-Tuning**|PEFT, Axolotl, RLHF adapters| |**Inference**|vLLM, FastAPI, Triton, Modal| |**Evaluation**|Eleuther Eval Harness, TruthfulQA, MMLU, custom test suites| |**Governance**|OpenWeights, BentoML, Smart Contract Wrappers| --- ## Integration with rolodexter Ecosystem |Component|Role| |---|---| |**rolodexterVS**|Agent coordination layer and test scaffolding| |**rolodexterIDE**|Training interface, config templating, telemetry monitoring| |**rolodexterGIT**|Model versioning, traceable finetune checkpoints| |**rolodexterAPI**|Inference routing, model access control, usage auditing| |**rolodexterGPT**|Model tuning guidance, spec drafting, and evaluation synthesis| --- ## Principles - **Composable Intelligence**: All models are built as primitives for greater agentic architectures. - **Verifiability**: Outputs are auditable, traceable, and attachable to logic gates or consensus. - **Open-by-Default**: We support open-weight contributions, remixing, and federated deployments. - **Human-Centric Alignment**: Each model respects epistemic agency, cultural nuance, and fairness as core values. --- ## Availability Model development services are offered to: - Research orgs and think tanks - Decentralized scientific institutions - Founders building with AI - Public infrastructure networks (e.g. education, governance, DeSci)