CarperAI/trlx
GitHub ã§èŠãCollapse reference+learner hydra heads when using LoRa
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#320 opened on 2023幎2æ21æ¥
contributions welcomefeature requestgood first issue
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With additive (delta-style) parameter-efficient tuning methods such as LoRa, we should be able to make a slightly more mem-efficient hydra architecture by using a single block that does ~frozen_head + tunable_weights for the learner/policy head's fwd-pass and simply frozen_head for the reference, instead of maintaining 2x heads.
CC @LouisCastricato and @cat-state for pointing this out
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