Gemma-4-E4B-Uncensored-HauhauCS-Aggressive -> Genesis
⚡ Why Genesis project exists? During training, ALL models don't just learn knowledge - they also accumulate random noise in their tensors. This noise builds up and creates something I call the Noise Gate - a fundamental barrier that stops LLM models from learning further and makes them unstable, verbose, and prone to hallucinations. My approach reduces this noise. It repairs the signal without touching the learned knowledge and gradient. The result is a model that consistent in performance, context clarity and following instructions, because it's no longer fighting its own internal chaos.
This is Gemma-4-E4B-Uncensored-HauhauCS-Aggressive model. made by HauhauCS
upgraded via Genesis training noise distillation algorythm made by me.
Vision encoder is not included because it's unfixable and broken too much. Here stats.txt
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Specs
- 4B parameters
- 42 layers, mixed sliding window (512) + full attention
- 131K context
- Natively multimodal (text, image, video, audio)
- 18 KV shared layers for memory efficiency
- Based on HauhauCS/Gemma-4-E4B-Uncensored-HauhauCS-Aggressive
Recommended Settings
From the official Google Gemma 4 authors:
temperature=1.0, top_p=0.95, min_p=0.05, top_k=64
Important:
- Use
--jinjaflag with llama.cpp for proper chat template handling - Vision/audio support requires the
mmprojfile alongside the main GGUF
Usage
Works with llama.cpp, LM Studio, Jan, koboldcpp, and other GGUF-compatible runtimes.