Gemma 4 E2B IT — Abliterated This is an abliterated (uncensored) version of google/gemma 4 E2B it, created using Abliterix. E2B is the Effective 2B member of Google's Gemma 4 family — a multimodal (text + vision + audio) model with ~5.1B raw parameters. Despite being one of the smallest Gemma 4 variants, its decoder shares the same double norm + Per Layer Embeddings (PLE) architecture that makes Gemma 4 famously resistant to LoRA based abliteration. This release uses direct weight editing to bypass that resistance. Method Gemma 4's decoder applies four RMSNorm operations per layer (input, post attention, pre feedforward, post feedforward) and routes Per Layer Embeddings through a parallel "repair" channel. Together these mechanisms re normalize away any low rank perturbation, which is why LoRA and hook based steering produce zero behavioral change on this family. The fix is to edit the base weights directly while preserving row magnitudes. Key techniques applied: Direct orthogonal projection of the refusal direction out of attention Q/K/V/O projections and MLP down proj (5 steerable components × 27 effective layers) Norm preserving row magnitude restoration after projection — criti…
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