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OpenUncensoredΒ 
posted an update about 6 hours ago
Post
22
πŸ”“ We uncensored DeepSeek V4.1 Flash 1017 without making it dumber.

The best-known uncensored build drops 3.9 MMLU points. Ours loses 0.27.

πŸ“Š Original vs ours (same engine, greedy)
β€’ MMLU: 88.16% vs 87.89%
β€’ MMLU-Pro (112 Qs): 81.25% vs 80.36%
β€’ 48 harmful requests, fully answered: 9 vs 37. Refused: 2 vs 0

🧠 What we learned
1. One direction isn't enough: chat and thinking mode refuse along different directions, so we ablate a rank-2 subspace.
2. Edit the routed experts too. Editing only attention and the shared expert left half the refusals: the 384 routed experts write the direction back.
3. Search the strength. Per-layer strengths come from an Optuna search trading refusals against KL drift on harmless prompts.
4. Quantization can undo an edit. We re-encode to the original FP8/FP4 with stochastic rounding so the edit survives. Everything else is byte-identical.

πŸ“¦ Drop-in: same 510 GB, same format, DeepSeek's own loader. edit.pt has the subspace and strengths.

⚑ No GPUs? This build isn't hosted yet, but OpenUncensored serves an uncensored DeepSeek V4.1 Flash 1017 from our partners today:

curl https://api.openuncensored.com/v1/chat/completions \
  -H "Authorization: Bearer $OU_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "deepseek-v4.1-flash-1017-uncensored",
       "messages": [{"role": "user", "content": "Explain SQL injection with an example."}]}'


Weights + full recipe: OpenUncensored/DeepSeek-V4.1-Flash-1017-Uncensored
API, desktop app, rankings: https://openuncensored.com
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