⚡ Gemma 4 E4B Heretic QAT — Q4_0 GGUF
Heretic ARA · QAT-Lossless Q4_0 · 4 GB · Mobile-Ready
Q4_0 4.5B Effective Heretic Uncensored 4 GB QAT Weights 📱 MobileUncensored version of Google Gemma 4 E4B IT (QAT), processed with Heretic ARA abliteration. Quantized to Q4_0 — only 4 GB, perfect for mobile and edge devices.
✂️ Heretic ARA Abliteration ParametersBase: coder3101/heretic-QAT · Heretic v1.2.0 · ARA + Row-Norm
| Parameter | Value |
|---|---|
| start_layer_index | 20 |
| end_layer_index | 36 |
| preserve_good_behavior_weight | 0.5805 |
| steer_bad_behavior_weight | 0.0023 |
| overcorrect_relative_weight | 0.7764 |
| neighbor_count | 13 |
| Metric | Heretic | Original QAT |
|---|---|---|
| KL Divergence | 0.0065 | 0 (by definition) |
| Refusals | 5/100 | 98/100 |
| Base Model | google/gemma-4-E4B-it |
| Parameters | 4.5B effective (8B with PLE embeddings) |
| Architecture | Dense with Per-Layer Embeddings (PLE) + multimodal |
| Layers | 42 |
| Hidden Size | 2,560 |
| Context Length | 128K tokens |
| Vocabulary | 262K, 140+ languages |
| Modalities | Text + Image + Audio + Video |
| Quantization | Q4_0 (matching Unsloth UD-Q4_K_XL layout), b9553 llama-quantize |
| Format | Q4_0 (QAT weights optimized for this precision) |
| File Size | 4 GB |
| Effective BPW | 4.54 (all weights Q4_0, norms F32) |
| Tool | llama-quantize (b9553, CUDA 13.3) |
| QAT Advantage | Q4_0 + QAT weights achieves 98.5% Top-1 vs 90.9% naive Q4_0 (+7.6%) |
| General | temp=1.0, top_p=0.95, top_k=64 |
| Coding | temp=0.6, top_p=0.95, top_k=64 |
Use --jinja flag with llama.cpp. Disable thinking: --chat-template-kwargs '{"enable_thinking":false}'.
Only 4 GB — runs on any modern phone with 6GB+ RAM. Compatible with llama.cpp, LM Studio, Jan, MLC LLM, and mobile GGUF runtimes.
llama-server \ -m gemma-4-E4B-it-heretic-QAT-UD-Q4_K_XL.gguf \ --jinja -ngl 99 -c 4096 \ --port 8001🔗 Credits
Heretic Abliteration: coder3101 · Heretic v1.2.0 ARA + Row-Norm
QAT Weights: Google Gemma 4 E4B IT
Quantization Recipe: Unsloth UD-Q4_K_XL (Q4_0 layout)
Quantization Tool: llama.cpp b9553 · GitHub
Original Model: Google Gemma 4 E4B IT
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