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Jim Lai

grimjim
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Experimenting primarily with 7B-12B parameter text completion models. Not all models are intended for direct end use, but aim for research and/or educational purposes. Recent Contributions: stabilized refusal direction ablation via Gram-Schmidt orthonormalization and norm-preserving interventions; confirmed reasoning transfer via model merger.

Recent Activity

posted an update 1 day ago
I tinkered a bit with refusal ablation after seeing this article that proposed using optimal transport. https://arxiv.org/abs/2603.04355 Title: Efficient Refusal Ablation in LLM through Optimal Transport Authors: Geraldin Nanfack, Eugene Belilovsky, Elvis Dohmatob While closed Bures-Wasserstein sounded cool, the use of top-K at low K implied that the approach likely wouldn't capture refusal in detail, and increasing KL divergence with greater K suggested that the approach was too damaging for latent reasoning. I tried it out, and the results were disappointing.
repliedto BoldingBuilds's post 25 days ago
Abliterated thinking models have a habit: they decide what to say, then keep arguing with themselves until the token budget runs out. Qwen3.8-27B Abliterated ThinkFix is an uncensored Qwen3.8-27B with one output row edited so the model closes its thinking when it's ready to answer. On 40 sensitive prompts the edit never saw, 8k output cap: 33 replies finished cleanly instead of 22, 5 hit the limit instead of 17, 61 minutes for the set instead of 75. Agent use was checked four ways and the edit changes nothing there. MTP draft head kept. Q4_K_M to Q8_0, each tested after the edit. The card lists what the edit was fit on and what it does not do. https://huggingface.co/BoldingBuilds/Qwen3.8-27B-Abliterated-ThinkFix-GGUF
updated a collection about 2 months ago
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