# Explore language models with Drowse

Drowse brings language-model generation, activation steering, and mechanistic interpretability into one workbench. These guides connect the visible controls to the experiments you can run and the limits of their measurements.

Resource: https://drowse.ai/learn.md

## Start with a model and a question

Open the browser app, run its device check, and choose a compatible model. A chat model follows a conversation template; a base model continues raw text. Generate a baseline before changing the prompt, sampling settings, or internal activations.

- [Browser models and requirements](https://drowse.ai/learn/browser-models.md)
- [Open Drowse](https://drowse.ai/app)

## Choose an experiment



- Inspect a token's alternatives, its probe and feature readings, and what each layer reads and says through the S and R lenses.
- On Gemma 3 and Qwen3 models, find the neurons and heads that pushed a token, read what one writes, and push a neuron or silence a neuron or head.
- Steer with a concept, a manifold position, a lens word, an SAE feature, or a single neuron, during the whole reply or only part of it.
- Branch from a turn or token and compare continuations under controlled settings.
- Score named completion choices to inspect a distribution rather than only the sampled answer.

- [Token and representation inspection](https://drowse.ai/learn/interpretability.md)
- [Activation steering guide](https://drowse.ai/learn/activation-steering.md)
- [Branching and comparison guide](https://drowse.ai/learn/experiments.md)

## Find your way around

The header holds six rooms. The Workbench is where you talk to the model, with the Inspector beside the conversation. Three more read the same conversation token by token: Units (neurons and heads), Lens (each layer through both lenses) and Probes (concepts, manifolds and SAE features), and a token chosen in one is the token in the others. Artifacts is where you fit, fetch and build what they read with: packs, probes, templates and roles. Model holds the model's layers, units, device and what is prepared for it.

- [The dashboard](https://github.com/stdlogits/drowse/blob/main/README.md#the-dashboard)

## Extend the workbench

The hosted browser edition runs locally with WebGPU. The Python edition adds a programmatic interface, inference APIs, and instrument authoring: fitting lenses, training SAEs and fetching published unit catalogs. Visiting browser agents can use Drowse's experimental WebMCP tools when their browser supports them.

- [Developer and agent guide](https://drowse.ai/developers.md)
- [Project documentation](https://github.com/stdlogits/drowse/blob/main/README.md)

[Documentation index](https://drowse.ai/llms.txt) · [Open Drowse](https://drowse.ai/app) · [Source code](https://github.com/stdlogits/drowse)