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There is even a fork of nanoGPT which might serve as a great reference:
https://github.com/BlinkDL/nanoRWKV
First we will have to make the attention modular, and allow a a b c style mixtures of attention layer types (with and without weight tying).
Afterwards we should be able to perform a Hymba like approach to mixing language model types.
The text was updated successfully, but these errors were encountered:
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There is even a fork of nanoGPT which might serve as a great reference:
https://github.com/BlinkDL/nanoRWKV
First we will have to make the attention modular, and allow a a b c style mixtures of attention layer types (with and without weight tying).
Afterwards we should be able to perform a Hymba like approach to mixing language model types.
The text was updated successfully, but these errors were encountered: