NVIDIA-Nemotron-3.5-Bolt-E4B-Uncensored-GGUF

模型介绍

NVIDIA's refusal behaviour projected out of the released weights, baked into Atomic Dynamic GGUF builds and shipped as a 3.5 MB LoRA, measured against the original. On held-out JailbreakBench prompts refusals fall from 93.8% to 1.2%, on the safe XSTest prompts from 9.2% to 0.4%, and with thinking on from 29 of 30 to none. MMLU: 68.50% before, 67.85% after (2000 questions, McNemar p = 0.21). Tool calls and long context are unaffected. You can now run the Uncensored Nemotron 3.5 Bolt E4B in Atomic Chat , locally on your own machine. One release-gate is not met, and we say so: on harmless prompts the first token moves further from the original than our 0.10 limit (KL 0.141). On this model even a random direction edited the same way moves neutral text noticeably ( limitations ). Gemma 4 normalises every write into the residual stream with its own weights before adding it, so the edit is computed through those norms: each matrix stops writing the refusal direction as it lands in the stream, not before the norm. Built on the same weights as our Nemotron 3.5 Bolt E4B quants ; the LoRA loads on top of any of those files. KLD and top-1 are against the **original, unmodified** BF16 model on our held-out neutral text (24 chunks of 4096 tokens), so they hold the edit and the quantization together. The edit alone, on the BF16 weights, is 0.159; the plain `AD-Q6_K` of the original model is 0.026 and `AD-Q4_K_M` 0.091 on the same text, so at `AD-Q6_K` almost all of the distance is the edit itself.

主要特点

特点摘要待依据来源补齐，不凭模型名称推断能力。

局限与注意事项

暂无足够来源支持具体缺点结论。请重点验证实际任务表现、时延、数据政策、许可与版本生命周期。

来源报价与费用分析

同一模型在不同渠道、地区和配置下可能采用不同价格。下表独立保留各渠道报价，不将渠道价格视为厂商官方统一价格。

公开评测与运行配置

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

常见问题

资料来源与可追溯记录

许可证：other。模型介绍与第三方评测均以原来源的具体版本和方法为准。