Add README

README.md

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+---
+license: apache-2.0
+tags:
+  - sparse-autoencoder
+  - interpretability
+  - multimodal
+  - paligemma2
+  - llava
+---
+
+# MMDiff — Multimodal SAE checkpoints
+
+Text-only-masked SAEs trained on the residual streams of multimodal LLMs, used by the
+**MMDiff** multimodal model-diffing pipeline (code:
+[hunarbatra/MMDiff](https://github.com/hunarbatra/MMDiff), project page:
+[hunarbatra.com/MMDiff](https://hunarbatra.com/MMDiff/)).
+
+## Contents
+
+### `paligemma2/jumprelu_text_only/` — 26 layers
+JumpReLU SAEs (width 16,384) trained on `google/paligemma2-3b-mix-448` language-model
+residual stream, layers 0–25, with **text-only masking** (image-token positions are
+excluded from the training loss). Diffed against the Gemma-Scope base SAEs
+(`google/gemma-scope-2b-pt-res`, `width_16k`).
+
+File: `text-only_layer_{L}.pt` with keys `W_enc`, `b_enc`, `W_dec`, `b_dec`, `threshold`.
+
+### `llava_more/topk_text_only/` — 32 layers
+TopK SAEs (k=50, width 32,768) trained on
+`aimagelab/LLaVA_MORE-llama_3_1-8B-finetuning` residual stream, layers 0–31, with
+text-only masking. Diffed against the LLaMA-Scope base SAEs
+(`fnlp/Llama3_1-8B-Base-LXR-8x`, sae-lens release `llama_scope_lxr_8x`).
+
+File: `text-only_layer_{L}.pt` with keys `W_enc (4096×32768)`, `b_enc (32768)`,
+`W_dec (32768×4096)`, `b_dec (4096)`.
+
+## Loading
+
+```python
+import torch
+from huggingface_hub import hf_hub_download
+
+p = hf_hub_download(
+    "OX-PIXL/MMDiff_SAEs",
+    "paligemma2/jumprelu_text_only/text-only_layer_13.pt",
+)
+state = torch.load(p, map_location="cpu")
+```
+
+See the [MMDiff repo](https://github.com/hunarbatra/MMDiff) for the full pipeline
+(training, adapted-feature selection, task-specific discovery, ablation, steering).