Step 3 of 7 in Sequence
Model Selection & Fine-Tuning
Estimated Duration: 2 - 4 Weeks
Step 3 selects, benchmarks, and fine-tunes foundation models for your domain. We evaluate open-weights models versus proprietary APIs and apply LoRA fine-tuning for domain jargon.
Operational Deep-Dive
What Happens During Step 3
We run standardized benchmark evaluations (MMLU, domain test suites) across Claude 3.5, GPT-4o, and open-weights models (Llama 3, Qwen 2.5). When proprietary terminology is required, we execute PEFT/LoRA fine-tuning.
Why Sequence Matters:
Selecting and tuning the core intelligence engine ensures agent state loops in Step 4 operate on reliable model outputs.
Requirements & Artifacts
Client Inputs vs. Delivered Artifacts
What We Need From You (Inputs)
- Domain-specific training datasets (minimum 500 validated Q&A pairs).
- Evaluation criteria and target accuracy thresholds.
- Hardware preference (cloud API vs dedicated GPU instance).
What You Receive (Deliverables)
- Model Evaluation Benchmark Comparison Matrix.
- Fine-tuned Model Weights (if open-weights route selected).
- Prompt Template Library with Few-Shot Examples.
Next Phase in Sequence