---
license: apache-2.0
tags: [interpretability, activations, qwen3, delta-nla, natural-language-autoencoder]
pretty_name: Delta-NLA warm-start data for Qwen3-8B
---
# Delta-NLA warm-start data (Qwen3-8B)

Per-token, per-layer records of what one transformer block of **Qwen/Qwen3-8B** changed, built for training a
*Delta natural-language autoencoder*: a verbalizer that sees the residual stream before (X) and after (Y) a block
and a reconstructor that must recover the update Δ = Y − X from the description alone.

Code: https://github.com/syvb/metamodelling

## Files

- `fineweb/records.jsonl` — one record per (document, position, layer): norms, cosines, causal effect of removing the
  update (all / attention part / MLP part) on final next-token log-probs, attention sources. Layers 6, 12, 18, 24, 30;
  1,500 FineWeb documents × 3 positions.
- `fineweb/vec_*.npz` — fp16 vectors per record: `X` (input to the block), `d` (= Y − X), `d_attn`, `d_mlp`; `ids` aligns with `records.jsonl`.
- `fineweb/docs.jsonl` — token ids of each (randomly truncated, ≤512 tokens) document.
- `fineweb/evidence.jsonl` — human-readable evidence per record: decoded tokens, fixed-scale logit-lens readings,
  lens probability shift, per-layer percentiles, source snippets (clipped at the current token), 1200-char context.
- `fineweb/mean_d.pt` — per-layer mean update vectors (subtract before computing variance explained).
- `fineweb/descriptions_*.jsonl` — natural-language descriptions of each update written by `openai/gpt-5.6-luna` from the
  evidence only (never the true next token). `v34` = thought-style prompt (no token quotes); `v1_partial` = token-quoting prompt.
- `math/` — the same for 16 one-pass arithmetic / multi-hop prompts at **all 36 layers**, last two positions.

## Conventions
Activations are Qwen3-8B residual stream, `hidden_states[n]` = input to block n. Lens of an update is
`W_U (g ⊙ Δ / rms(X))`. Causal effect = final log-probs with the update at that position replaced by nothing
(all), by the MLP part only (attention removed), or by the attention part only (MLP removed).