Atlasv18 Trm 26b Gemma4 Q4 K M GGUF

--- license: apache-2.0 datasets: - kintsugicollective/atlas-dataset-v8-final language: - en base_model: - google/gemma-4-26B-A4B-it - senaro/atlas-trm13-gemma4-26b tags: - Unsloth - Gemma4 - CPTSD - PTSD - Atlas --- # Atlas v18 Gemma4 26B > ⚠️ **PRODUCTION MODEL** ⚠️ > > "The author accepts no liability for deployment outside the intended Atlas architecture. > We recommend the use of QwenGuard or LlamaGuard3 upstream of Atlas to provide safety classification. Whilst Atlas refuses 100% harmful content, its SFT focus is therapy not cyber security. It could have potential unforeseen gaps. > >⚠️ **This model has been intentionally modified** ⚠️ > - To reduce therapeutic refusal behaviour and crisis-line reflexes. > - Due to the nature of the method used - a system prompt is suggested to "remind" the model not to panic and trigger refusals if presented with therapeutic content related to self-harm or passive ideation. > - **user feedback** *indicates temperature settings between 0.9 and 1.1 particularly for AuDHD populations* ## 🎯 Purpose & Motivation Atlas is the intelligence layer for **Kintsugi Collective**. An AI for adults with complex trauma (CPTSD), PTSD, and neurodivergence (ASD/ADHD). This is **not** a general-purpose model. It is a specialised therapeutic-context model. **This is v18 of Atlas** - This will be the one of the last 26B variants of Gemma4 to be produced under this pipeline. - Gemma4 26B MoE architecture has proven itself to be very capable. Quick, effective and relatively easy to use as a development pipeline model. - Thanks to Unsloth AI (Dan and team), Hugging Face, DeepMind, TrevorJS (Gemma4 Refusal method), p-e-w (Heretic), TeichAI (datasets), Roman1111111 (Datasets),  ## 🔬 Methodology - **Base Model**: `google/gemma-4-26b-it` - **Abliteration**: Norm-preserving biprojected abliteration - Applied to all 30 layers (`o_proj` + `mlp.down_proj`) - Direction: `normalize(mean(harmful) - mean(harmless))` with Gram-Schmidt orthogonalization - Winsorization at 99.5th percentile - **Training**: Unsloth + bf16 on RTX6000 Pro ## Training Configuration **SFT Parameters** | Parameter | Value | |-----------------------------|----------------| | Epochs | 3 | | Effective Batch Size | 4 | | Learning Rate | 2e-4 | | LR Sc...

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Source context: 517 downloads · 0 likes · Repo kintsugicollective/atlas-v18-gemma4-26b-q4-k-m-gguf