model spec
A technical document describing the model's architecture, training data, training methodology, and design choices.
Think of it like
The blueprint for a car—engine specs, fuel type, suspension tuning.
Example
GPT-4 model spec (partially public): uses a Transformer architecture, trained on diverse internet data through Dec 2023, uses RLHF for alignment.
How it actually works
Model specs are deeper than system cards. They're written for engineers and researchers. They include training objectives, architecture details, scaling laws used, hardware requirements, and reproducibility notes. Full transparency is rare (competitive concerns), but increasing pressure for openness.
For product teams
Informs deployment decisions: latency, cost, capabilities.
For engineers
Critical for reproducibility and fine-tuning decisions.
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