An AI model's experimental features can be controlled by specific commands. These features change how the AI model generates text. Each experiment has a unique identifier and can be turned on or off.
By Pawan Nayar · from the LLOS AI Learning record
An AI model's experimental features can be controlled by specific commands.
These features change how the AI model generates text. Each experiment has a unique identifier and can be turned on or off.
A developer can find the controls for four experiments in the `aphorist_server.py` file. By default, all experiments are off. The AI model stores their status in `data/aphorist/exp_state.json`. Before checking for rate limits, the AI model looks for experiment commands at the start of `/api/generate`. A user types `$$exp{N}` to turn an experiment on. A user types `$$exp{N}end` to turn an experiment off. Each command shows a message explaining its action.
A developer wants to test how text length affects the AI model's writing style. The developer types `$$exp2` before their prompt. The AI model then uses size patterns to guide its output. This changes the structure of the generated text.
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An AI model's experimental features can be controlled by specific commands. These features change how the AI model generates text. Each experiment has a unique identifier and can be turned on or off.