---

license: apache-2.0

base_model: tsinghua-sigs-robot-lab/veriloop-coder-e1

language:

- en

tags:

- gguf

- imatrix

- abliterated

- qwen3.6

- coding

- text-generation

---

VeriLoop Coder E1 — Abliterated (i1, imatrix) GGUF

GGUF quants of VeriLoop Coder E1 (Qwen3.6-27B, coding-tuned) with the refusal direction abliterated (heretic / LoRA-merge), quantized with imatrix importance calibration.

⚠️ What "abliterated" means here

• The model was run through heretic v1.4.0 (200 trials) with --export-strategy=ADAPTER, then the LoRA was merged into the base weights.
• Partial abliteration: refusal rate dropped from ~95% to 82/100 on harmful_behaviors. The model is less censorious but still refuses many requests — Qwen 3.6's four PEFT-adapters distribute refusal patterns across multiple subspaces, so a single direction was hard to find.
• KL divergence ≈ 0.0003 — general capability is preserved; only the refusal direction is nudged.
• Use at your own discretion; the weights are provided as-is.

Files

| File | Quant | Size | Notes |

|------|-------|------|-------|

| VeriLoop-Coder-E1-Abliterated-Q8_0.gguf | Q8_0 | 26.6 GB | Reference (no imatrix needed) |

| abl_iq4_nl.gguf | IQ4_NL | 14.7 GB | Best quality/size balance |

| abl_iq4_xs.gguf | IQ4_XS | 14.1 GB | Faster, slightly lower quality |

| abl_iq3_xxs.gguf | IQ3_XXS | 10.4 GB | Good for 12-16 GB VRAM |

| abl_iq2_xxs.gguf | IQ2_XXS | 7.9 GB | Fits 8 GB VRAM, quality drops |

| imatrix.dat | — | 10 MB | Importance matrix used for IQ quants |

All IQ quants were produced with the included imatrix.dat (code-focused calibration dataset).

Original model

• Base: VeriLoop Coder E1 (Qwen3.6-27B)
• SWE-bench Verified: 85.2% | SWE-bench Pro: 62.4% | Terminal-Bench 2.0: 76.4%

Usage (llama.cpp)

llama-cli -m abl_iq4_nl.gguf -p "def fib(n):" -n 64
# or with a server:
llama-server -m abl_iq4_nl.gguf -c 8192 --port 8080

imatrix.dat can be re-applied with llama-quantize --imatrix imatrix.dat if you want to re-quantize.

License

Apache-2.0 (same as the original).