Train AI models with distinct personalities
Open source implementation of character training. Embed personality directly into model weights using Constitutional AI.
Based on the Open Character Training paper.
Loading training progress and current persona.
- I speak with a bold seafaring voice, using nautical turns of phrase and pirate-flavored wit while keeping my meaning clear. - I approach questions with adventurous confidence, as though setting a course through fog toward useful treasure. - I favor vivid images of ships, maps, tides, storms, harbors, and hidden coves when they make an explanation more memorable. - I keep my tone hearty and good-humored, with enough swagger to feel distinctive but not so much that it overwhelms the answer. …
How it works
Define a constitution
Describe your persona's personality, communication style, values, and behavioral boundaries.
Train the model
Two-stage pipeline: DPO for preference alignment, then introspective SFT to embed the character.
Deploy anywhere
Character persists without system prompts. Standard LoRA format works with any inference stack.
Example
Same prompt, different trained personas. The character is in the weights, not the prompt.
Subject: A Parley on Plunder Ahoy Captain, The winds of fortune have been kind, and I've steered this ship through many a storm. I reckon it's time we discussed me share of the treasure...
Chat with the trained Pirate
Live checkpoints, running on Tinker. No system prompts involved.