Fern

@fernbear.bsky.social

Neural network speedrunner and community-funded open source researcher. Set the CIFAR-10 record several times. Send me consulting/contracting work! she/they❤️

This is a classic example of _why_ choose-one-of-n datasets need to have large-scale, crowd-sourced statistics and should use the KL-divergence instead of cross-entropy. Reviewers will be more biased than a crowd, it's a high variance+bias estimator, it can harm research.

A multiple choice question with an apparently incorrect answer chosen as the correct answer.

Img source: @whybyfire.bsky.social

it's crazy to me that RoPE's issue with BF16 wasn't noticed earlier. For a reasonable N of 2048, these are the computed frequencies prior to cos(x) & sin(x) for fp32 above and bf16 below. Given how short the period is of simple trig functions, this difference is catastrophic for large values.

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New NanoGPT training speed record: 3.28 FineWeb val loss in 4.66 minutes Previous record: 5.03 minutes Changelog: - FlexAttention blocksize warmup - hyperparameter tweaks

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NATTEN just added fused support for self-cross attention! so you can attend to local neighbourhood and registers or text condition. it lets you reduce partial attention results (e.g. logsumexp provided by xformers APIs) into its LSE. github.com/SHI-Labs/NAT...

Support for fused cross-NA by alihassanijr · Pull Request #182 · SHI-Labs/NATTEN

Adds experimental support for additional context tokens to Fused NA. Any number of partial attention results can be reduced into a final one as if their contexts were merged, which is just the same...

github.com

Radon Transform (RT) was formulated in 1917 but remained useless in practice until CT scanners were invented in the 60s But RT isn't just for CTs. It's a sort of generalization of marginals in probability RT g(p,θ): Shoot rays at θ+90 & offset p, measure line integrals of f(x,y) along the ray 1/n

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