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config: docstrings say default is pre-fitted RAW lens, chat_corpus is fallback-only

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Fresh-eyes caught stale framing: the module/chat_corpus docstrings still sold chat-
templated fitting as the corpus convention. The default demo path now loads the
authors' pre-fitted raw-wikitext lens; chat_corpus only feeds the local-fit fallback,
and chat-vs-raw was never compared head-to-head (run-524 used chat), so it's flagged
unresolved rather than claimed better.

Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
This commit is contained in:
wassname
2026-07-10 19:24:51 +08:00
co-authored by Claudypoo
parent 220f5018ac
commit 99b50695bd
1 changed files with 12 additions and 9 deletions
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config.py
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@@ -1,10 +1,10 @@
"""Repo-local paths, slug/cache conventions, and the fit corpus, shared by
scripts/ and notebooks.
"""Repo-local paths, slug/cache conventions, and the pre-fitted lens map, shared
by scripts/ and notebooks.
NOT imported by the jsteer library (which stays path-agnostic so `pip install
jsteer` never needs a repo root). The corpus content is jlens's own WikiText
(`load_wikitext_prompts`, not hand-rolled), but wrapped in the model's chat
template -- see chat_corpus for why.
jsteer` never needs a repo root). The default demo path LOADS a pre-fitted lens
(HUB_LENS_FILE, raw Salesforce-wikitext); chat_corpus is only for the local-fit
fallback (scripts/fit.py) and is an untested alternative to raw -- see its docstring.
"""
from pathlib import Path
@@ -49,10 +49,13 @@ def hub_lens_file(model_name: str) -> str:
def chat_corpus(tok, n_prompts: int) -> list[str]:
"""jlens's WikiText prompts wrapped in the chat template. Fitting on chat-
formatted text (not raw documents) puts J closer to the distribution the
model steers in; run-524's verified vectors were fit this way too. Called
via a lambda in fit_cached, so it only downloads WikiText on a cache miss."""
"""jlens's WikiText prompts wrapped in the chat template, for the LOCAL-FIT
fallback only (the default demo path loads the authors' pre-fitted RAW-wikitext
lens). Hypothesis: fitting on chat-formatted text puts J closer to the
distribution we steer in; run-524's verified vectors were fit this way, but it
was never compared head-to-head with a raw fit, so treat chat-vs-raw as
unresolved. Called via a lambda in fit_cached, so WikiText only downloads on a
cache miss."""
from jlens.examples import load_wikitext_prompts
return [tok.apply_chat_template([{"role": "user", "content": p}],
add_generation_prompt=True, tokenize=False,