Add dataset card

README.md

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+---
+license: other
+pretty_name: Crosscoder Multilayer Split Activations
+tags:
+  - mechanistic-interpretability
+  - crosscoder
+  - activations
+  - sparse-autoencoder
+---
+
+# Crosscoder Multilayer Split Activations
+
+Raw split activation artifacts for multilayer SPARC-style crosscoder training.
+
+This dataset stores reusable base-only and aligned-only activation tensors. These
+are intended to be assembled into matched `activations.pt` training artifacts
+before crosscoder training.
+
+## Versions
+
+### v1
+
+Source local run: `interp_utils/crosscoder/results-multi-v1`
+
+Layout:
+
+```text
+v1/
+  base_activations/
+    smollm3-union/
+    llama32-3b-union/
+    qwen3-4b-union/
+  aligned_activations/
+    smollm3-{dpo,grpo,kto,orpo,ppo,simpo}/
+    llama32-3b-{dpo,grpo,kto,orpo,ppo,simpo}/
+    qwen3-4b-{dpo,grpo,kto,orpo,ppo,simpo}/
+```
+
+Each run directory contains:
+
+```text
+run_meta.json
+activations/base_activations.pt      # base-only runs
+activations/aligned_activations.pt   # aligned-only runs
+```
+
+The base tensors contain union layer sets. The aligned tensors contain each
+aligned model's target probe-best layer window. Assembly slices/reorders the
+base union tensor to the aligned run's layers.
+
+## v1 Base Layers
+
+```text
+smollm3-union:      [16, 17, 18, 19, 20]
+llama32-3b-union:   [10, 11, 12, 13, 14, 23, 24, 25, 26]
+qwen3-4b-union:     [19, 20, 21, 22, 23, 24, 25]
+```
+
+## Use
+
+Download one base union and one aligned run, then assemble locally with:
+
+```bash
+.venv/bin/python -m interp_utils.crosscoder.main \
+  --stage assemble \
+  --crosscoder-kind multilayer_sparc \
+  --base-activations-dir path/to/base_union_dir \
+  --aligned-activations-dir path/to/aligned_run_dir \
+  --output-dir path/to/assembled_run_dir
+```
+