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Intermediate Activations – the forward hook (2020)

41 点作者 reqo大约 1 年前

4 条评论

vinay427大约 1 年前
For those interested in playing with or doing research using model internals, the TransformerLens [1] project appears to be the leading open-source tooling in this area. It allows for loading dozens of different models, adding hooks, displaying activations in a format compatible with CircuitsVis, and other (mechanistic) interpretability work.<p>[1] <a href="https:&#x2F;&#x2F;github.com&#x2F;neelnanda-io&#x2F;TransformerLens">https:&#x2F;&#x2F;github.com&#x2F;neelnanda-io&#x2F;TransformerLens</a><p>[2] <a href="https:&#x2F;&#x2F;github.com&#x2F;alan-cooney&#x2F;CircuitsVis">https:&#x2F;&#x2F;github.com&#x2F;alan-cooney&#x2F;CircuitsVis</a>
knlb2022大约 1 年前
I gave a small talk on how to really push using hooks for logging intermediate values (including capturing gradients from torch &amp; fx scripted modules) that may be useful: <a href="https:&#x2F;&#x2F;static.sched.com&#x2F;hosted_files&#x2F;pytorch2023&#x2F;40&#x2F;Intermediate%20Logging%20_%20PyTorch%20Conference%202023.pdf" rel="nofollow">https:&#x2F;&#x2F;static.sched.com&#x2F;hosted_files&#x2F;pytorch2023&#x2F;40&#x2F;Interme...</a>
jph00大约 1 年前
FYI, for anyone interesting in creating and using hooks to better understand what&#x27;s happening in your model, I created a free lesson covering that:<p><a href="https:&#x2F;&#x2F;course.fast.ai&#x2F;Lessons&#x2F;lesson17.html" rel="nofollow">https:&#x2F;&#x2F;course.fast.ai&#x2F;Lessons&#x2F;lesson17.html</a>
jey大约 1 年前
(2020)