Add sub-1.5bpe frontier + entropy-bpe kernels and result sidecars#42
Merged
Conversation
…ars (Mistral/Llama/Qwen3 + Mistral NIAH) Lands four reproducibility kernels + six result JSONs: - nq_mistral_subbpe: Mistral-7B-Inst-v0.3 AQUA-iso PPL + live zstd-L22/Shannon bpe (K3V2 to K1V1 pb=0) - nq_llama31_subbpe: Llama-3.1-8B-Inst same protocol; rope_scaling propagated via prepare_rope_scaling() - nq_qwen3_subbpe_entropy: Qwen3-8B (NF4 weights) K3V2/K2V2 pb=0/pb=1 with entropy-coded bpe measurement - nq_mistral_niah_frontier: Mistral-7B-Inst-v0.3 chat-template NIAH at 4K+8K across six quant configs Result sidecars in experiments/kaggle/results/ confirm the sub-1.5bpe PPL frontier and NIAH cliff data cited in the paper. All kernels use ungated model mirrors; no HF_TOKEN required.
|
You have reached your Codex usage limits for code reviews. You can see your limits in the Codex usage dashboard. |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Summary
experiments/kaggle/results/so numeric claims are traceable to runsKernels
nq_mistral_subbpenq_llama31_subbpenq_qwen3_subbpe_entropynq_mistral_niah_frontierAll kernels use ungated model mirrors; no HF_TOKEN required on secondary accounts.
Result sidecars
Six JSONs in
experiments/kaggle/results/covering Mistral, Llama-3.1, Qwen3, Yi and HQMQ comparison runs.Sanitization
jagmardropinternal account name from comment lines (lines 8/33 Mistral, line 8 Llama)# From CLAUDE.md:block with 3 lines of internal context from Qwen3 kernel headerkernel-metadata.jsonid fields retainjagmardrop/namespace (Kaggle push requires it)os.environ.get("HF_TOKEN")); None is fine for ungated modelsProof of work