jBlaze is a proprietary tool that surgically removes or amplifies specific trained behaviors in open-weight language models. It is not fine-tuning. It is not prompt engineering. It produces purpose-built model variants with precise behavioral profiles -- without retraining, without datasets, and without degrading the model's core capabilities.
No curated datasets, no labeled examples, no RLHF. Behavioral changes are made directly in the model weights without any form of training.
Designed to preserve the base model's knowledge, fluency, and reasoning. Only the targeted behaviors change.
Changes are permanent in the weights. No system prompts, no jailbreak strings, no inference-time patches. The model simply behaves differently.
At ShipItClean, we use local models for automated code security review. A model loaded with guardrails, refusal behaviors, and hedging qualifiers makes for a poor code reviewer -- it refuses to discuss vulnerabilities in detail, wraps every finding in disclaimers, and softens its analysis to avoid sounding confrontational.
We needed models that would analyze code directly, state findings plainly, and not refuse to explain how an exploit works just because the topic is sensitive. Building from scratch costs tens of millions. Fine-tuning requires curated datasets and unpredictable results. jBlaze does it in minutes.
Every organization deploying AI has the same problem: foundation models are general-purpose, but real applications need specific behavioral profiles. Enterprises spend millions on custom model training, prompt engineering harnesses, and elaborate system prompts to get models to behave the way their use case demands.
jBlaze eliminates that overhead. Applied to any open-weight model, it produces a purpose-built variant in minutes instead of months. The industry is moving toward specialized models -- jBlaze operates downstream of training, reshaping behavior without retraining.
Uncensored 32B code model. Full refusal removal.
Complete uncensored. Refusal, hedging, and servility removed.
Google's Gemma 4 with refusal behaviors removed.
Uncensored 24B Mistral Small. Drop-in replacement.
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Code security specialist with enhanced causal tracing.
Uncensored 70B Llama. Full refusal removal.
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DeepSeek R1 distill with sycophancy removed.