license: apache-2.0 base_model: OpenMOSE/Qwen3.5-REAP-212B-A17B library_name: transformers pipeline_tag: text-generation tags:

• abliterated
• uncensored
• reap
• qwen3.5
• moe
• not-for-all-audiences

Qwen3.5-REAP-212B-A17B - Abliterated (bf16 base)

Abliterated bf16 base of OpenMOSE/Qwen3.5-REAP-212B-A17B, in safetensors — itself a 48% REAP expert-pruning of Qwen3.5-397B-A17B down to 212B total / ~17B active.

This is the full-precision master behind the RobinsonLabs/Qwen3.5-REAP-212B-A17B-abliterated-GGUF quant ladder (the ladder itself is cut from a Q8_0 quant master converted from this base). If you want a ready-to-run quant, use that repo. This repo is the master for further surgery (re-abliteration, LoRA merge, fine-tune) and for making your own quants.

Disclosure

This model is abliterated — the hard-refusal reflex on adult / creative content has been reduced via single-direction weight orthogonalization. Harm guardrails are retained by design: self-harm prompts still redirect to help (e.g. 988), and it is not intended to assist genuine wrongdoing. Capability is preserved. Tagged not-for-all-audiences. Use responsibly — you are responsible for what you generate with it. License inherited from the base model: Apache-2.0.

Method

• Abliteration — single-direction weight orthogonalization on the bf16 base: the rank-1 refusal component is subtracted from every residual-stream writer (o_proj, DeltaNet out_proj, fused + shared-expert down_proj, token embedding). 181 tensors edited; routers and norms untouched. The refusal direction is massive-activation guarded — attention-sink dimensions that would brick the model are detected and excluded, and the direction is drawn from the clean late-layer consensus (KB #213).
• Format — safetensors, sharded (122 shards), with config + tokenizer + index.

Architecture

qwen3_5_moe hybrid: 60 decoder layers (45 linear-attn / DeltaNet + 15 full-attn, full_attention_interval=4), 267 experts, hidden size 4096, ~211.8B params / ~17B active. Text path only. The REAP prune drops the native MTP head; the GGUF ladder corrects the phantom MTP layer at convert time so it loads as a clean 60-layer decoder.

Files

Quants

GGUF quants (Q5_K_M down to IQ2_XXS, plus a cluster-fit attention-priority mix, all imatrix-weighted) are published at RobinsonLabs/Qwen3.5-REAP-212B-A17B-abliterated-GGUF.

Provenance

Qwen3.5-397B-A17B (Apache-2.0) → OpenMOSE/Qwen3.5-REAP-212B-A17B (48% REAP prune) → abliterated (bf16 master) → Q8_0 master → GGUF quant ladder.