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Fork of IRIS, where instead of a new transformer as a world model we use an adapter on a pre-trained LLM. The hypothesis is that the pre-trained LLM will help the world model learn faster and in a more data-efficient manner.
Fork of IRIS, where instead of a new transformer as a world model we use an adapter on a pre-trained LLM.
The **hypothesis** is that the *pre-trained LLM will help the world model learn faster and in a more data-efficient manner*.
See also:
- [AdaVAE](https://github.com/ImKeTT/AdaVAE)