Model Lens

optional

See what a model is computing internally — the top vocabulary prediction at every internal site, for every token position. Models publish a stack-neutral BLAH Lens Bundle; this platform renders it.

Models with a published lens

ModelFrameworkSitesExecutionConformance
Alpha 60M Chat
ajaxdavis/alpha-60m-chat@ab1c5be13a12
alpha216remote_httppass
Steve Agent
MonumentalSystems/harmonic-gpt-128m-byte-agent-multiparty@368884ecb5db
custom-pytorch2remote_httppass
SpectralKAN Lohe SFT
MonumentalSystems/harmonic-gpt-spherical-kan-128m@eb83447f07c7
custom-pytorch2precomputed_onlypass
ANDREA-145M
russellbal/ANDREA-120M@6f81f00f9669
microgpt (CUDA-trained; first-party torch port microgpt/hf)13huggingfacepass
Lens Demo (synthetic)
blah-evals/lens-demo-synthetic@dede9a0e3737
demo16remote_httppass

What you get

                  The     capital  of      France   is
block.000.post    the     city     of      the      a
block.001.post    the     capital  of      France   the
block.002.post    a       capital  in      Paris    Paris

columns = token positions · rows = internal sites · cells = top readout

Readouts come in two flavours. The Logit Lens decodes a site directly, which is only valid when it is already in the basis the model's final decoding path expects. The Jacobian Lens first applies a fitted transport matrix, so sites of any width and basis become readable. A third mode shows where the two disagree.

The format says site, not "layer". A transformer's sites happen to be post-block residuals; a recurrent or state-space model's are not, and the grid must not imply they share semantics.

Add your model

The format is stack-neutral: nothing in it is named after or coupled to any framework. Bundles from PyTorch, JAX, MLX, Candle, Rust, Zig or a bespoke TypeScript engine are indistinguishable here. You keep your native implementation; you add a thin adapter.

Hand the prompt below to a coding agent in your model repository. It inspects your architecture, builds the adapter, fits the transports, validates, and prepares the Hugging Face upload.