README.md

---
pretty_name: ClimbMix Scored — Concept-Probe Detections (shards 25-49)
tags:
- interpretability
- probing
- gemma-2
size_categories:
- 1B<n<10B
---
# climbmix-scored-overflow

Concept-probe detection scores for **ClimbMix-shuffle shards 25-49** (nanochat
training data), gemma-2-2b layers 6/8/14 co-located per token, **FULL TOKEN
COVERAGE**: every parquet row appears in `docs_<sid>.jsonl`, no min-length
filter, no truncation — docs longer than 2048 gemma tokens are scored in
consecutive non-overlapping 2048-token windows (window-boundary context
truncation is an accepted artifact), so `sum(n)` equals the shard's total
gemma token count. Probes and quantization/standardization are FROZEN from
[corpus-scores](https://huggingface.co/datasets/kaushikreddyxyz/corpus-scores) (calibrated
once on shard 320 — never refit), so the two datasets are directly comparable
(note corpus-scores itself is first-2048-window only). Shard->repo map:
`assignment.json` (25 shards/repo, strictly in order across
8 repos). No DoM scores in this dataset family.

- `scores_<sid>.npy` int8 `[n_tokens, 3, 54]` — axis1: **0=L6, 1=L8, 2=L14**;
  axis2 = concept per `columns.json`. Dequant: `score = int8*scale[l][c]+zero[l][c]`.
- `tokens_<sid>.npy` int32 — full BOS-free gemma ids, docs in parquet order
- `docs_<sid>.jsonl` {doc, start, n} — n = full doc token count (0 allowed)
- Scoring: gemma-2-2b bf16 EAGER attention; probes from
  [concept-probes-gemma2-2b](https://huggingface.co/kaushikreddyxyz/concept-probes-gemma2-2b) gold_probes.