This repository hosts pre-fitted Jacobian-lens (J-Lens) adapters for
Miru Tracer. The files are created
with miru-tracer-fit-lens and let you use Miru's Jacobian-lens views without
spending hours fitting a lens for each model yourself.
[!IMPORTANT]
These are interpretability adapters, not LoRA adapters, fine-tunes, model
weights, or generation plugins. They do not change what a language model has
learned. They provide per-layer transformations that Miru uses to inspect—and
experimentally intervene on—the model's internal residual stream.
What is Miru Tracer?
Miru Tracer is an experimental,
open-source workbench for examining language-model generation token by token.
Its Gradio interface can:
step through generation and inspect token probabilities;
override, undo, or continue individual generation steps;
record and visualize complete generation traces;
apply a standard logit lens or a fitted Jacobian lens at intermediate layers;
compare logit- and Jacobian-lens readouts; and
experiment with steer, swap, and ablate interventions on readout directions.
See the Miru Tracer repository for
installation instructions, supported model families, and the full lens
tutorial.
What is a Jacobian lens?
A transformer builds its prediction through a sequence of residual-stream
states. Let h_l be the residual state at layer l, and let h_final be the
state immediately before the model's final readout.
A logit lens sends h_l directly through the model's final normalization
and unembedding. This is useful, but it implicitly assumes that an intermediate
state already lives in the same representational basis as the final state. That
assumption is often weakest in early and middle layers.
A Jacobian lens first transports the intermediate state toward the final
layer's basis with a fitted matrix:
J_l is the average Jacobian of the final residual state with respect to the
state at layer l, estimated over many calibration prompts and token positions.
The transported state can then be decoded with the model's own unembedding.
This often gives more meaningful early- and middle-layer readouts than applying
the unembedding directly.
Each adapter in this repository contains the fitted matrices for one exact base
model, plus fit metadata. The matrices are stored as safetensors; they do not
contain executable pickle payloads.
What fitting does
miru-tracer-fit-lens runs the base model over a calibration corpus, computes
Jacobians with repeated backward passes, and maintains a running average for
each fitted layer. Miru's default fitter:
considers up to 1,000 prompts;
uses sequences of at most 128 tokens;
waits for at least 100 successful prompts before early stopping;
tracks the mean relative change over the latest 10 successful updates; and
declares convergence when that rolling mean falls below 0.002.
The prompt count shown below is the number of successful prompts actually
included in the adapter—not merely the requested budget. Reaching the
convergence threshold means that the running Jacobian estimate stabilized under
this criterion; it does not by itself prove that every readout is
semantically correct.
Model compatibility
J-Lens adapters are model-specific. Use an adapter only with the exact model it
was fitted for. Two models can have the same hidden size and layer count while
still having different weights, tokenizers, and internal representations; a
shape match alone does not make their lenses interchangeable.
The Qwen/Qwen3.6-27B adapter was fitted against model revision 6a9e13bd6fc8f0983b9b99948120bc37f49c13e9 using the Ambiente Computacional Marie Curie (FINEP 01.22.181.00) at UFSCar.
More models and community contributors will be added over time.
Load the exact base model named in the table above.
Download its .safetensors adapter.
Open Miru's Lens tab and install the file in the Fit file section.
Select Jacobian or Compare (Jacobian / Logit) and generate or analyze
a sequence.
You can also install a file directly into Miru's lens cache. Miru converts the
slash in a Hugging Face model ID to -- for the cache directory, and expects
the installed artifact to be named lens.safetensors:
The fitter checkpoints after every successful prompt, so an interrupted run can
resume. The current partial average is also written as a usable
lens.safetensors file. Use --stop-at-delta 0 if you want to disable
convergence-based early stopping and force the full prompt budget.
Run the following for all options:
miru-tracer-fit-lens --help
Contributing an adapter
Community contributions are welcome. Please submit adapters as safe
.safetensors files using this path convention:
the exact Hugging Face model ID and revision, when available;
the number of successful prompts averaged;
whether the convergence criterion was reached or the run used a fixed budget;
any non-default fitting settings or calibration corpus;
the Miru Tracer version used to create the file; and
the contributor name and Hugging Face profile to display in the table.
Adapters generated by recent Miru Tracer versions embed model, tokenizer,
corpus, and convergence provenance where available. Please preserve that
metadata when uploading the artifact.
Public-domain contribution requirement
This repository is released under
the Unlicense, which dedicates the repository's
contents to the public domain. Every contributed adapter and its accompanying
metadata must be submitted under the same terms. A contribution cannot be
accepted under a more restrictive or additional license.
Because an adapter may be derived from a third-party base model or calibration
corpus, a contributor can dedicate only the rights they actually own. The
Unlicense does not cancel the base model's license, dataset terms, trademarks,
or any other third-party rights. Contributors are responsible for checking
those terms before submitting an artifact.
Every adapter contribution must include the following certification in its
Hugging Face pull request or discussion. Replace the final line with the
contributor's real name, Hugging Face username, and date:
Contributor Public-Domain Certification
I certify that I created this contribution or otherwise have the authority
to submit it. To the extent that I own copyright or related rights in the
adapter and its accompanying metadata, I permanently dedicate those rights to
the public domain under the Unlicense. Where a public-domain dedication is
not legally recognized, I make the contribution available under all
permissions and disclaimers stated by the Unlicense. I have disclosed the
base model and calibration sources, and I am not knowingly submitting
material that I lack permission to distribute. If I am contributing as part
of my employment or for another organization, I certify that I am authorized
to make this dedication on its behalf.
Signed-off-by: Full Name (@huggingface-username), YYYY-MM-DD
The Signed-off-by line records the contributor's affirmative agreement to
this certification; merely uploading a file is not sufficient. Maintainers may
request a separately signed waiver or proof of organizational authorization
for substantial or employer-owned contributions. The certification and
sign-off should be retained in the repository's contribution history.
Jacobians, lens readouts, and activation interventions are research tools. Fit
quality depends on the base checkpoint, calibration corpus, prompt count, and
fitting settings. Cross-check important conclusions with multiple methods and
do not treat an individual decoded token as a definitive explanation of a
model's internal computation.
