---

license: apache-2.0

base_model: openbmb/MiniCPM5-2B

language:

- en

- zh

library_name: gguf

pipeline_tag: text-generation

tags:

- minicpm

- minicpm5

- gguf

- llama.cpp

- text-generation

- abliterated

- uncensored

- on-device

- edge-ai

---

MiniCPM5-2B-heretic-abliterated-GGUF

This repository hosts quantized GGUF checkpoints based on openbmb/MiniCPM5-2B, implementing the directional refusal ablation methodology showcased in insraq/MiniCPM5-2B-heretic-abliterated via Heretic v1.4.0.

These builds are packaged for local on-device inference using llama.cpp, Ollama, LM Studio, Jan, and standard GGUF executors.

---

Abliteration Profile

Directional ablation neutralizes the refusal reflex across the residual stream and MLP projections while preserving the primary base model's mathematical, coding, and multi-step reasoning performance.

Benchmark Metrics

| Metric | Abliterated Model | Original Base (openbmb/MiniCPM5-2B) |

| :--- | :--- | :--- |

| Refusal Rate | 5 / 100 | 99 / 100 |

| KL Divergence | 0.0391 | 0.0000 (Reference) |

A low KL divergence of 0.0391 relative to the original openbmb/MiniCPM5-2B weights indicates minimal representation drift, preventing capability degradation on standard non-boundary tasks.

Ablation Parameters

| Parameter | Value | Parameter | Value |

| :--- | :--- | :--- | :--- |

| direction_index | per layer | mlp.down_proj.max_weight | 0.89 |

| attn.o_proj.max_weight | 1.47 | mlp.down_proj.max_weight_position | 28.68 |

| attn.o_proj.max_weight_position | 29.44 | mlp.down_proj.min_weight | 0.66 |

| attn.o_proj.min_weight | 1.45 | mlp.down_proj.min_weight_distance | 20.31 |

| attn.o_proj.min_weight_distance | 14.36 | — | — |

---

Available Quantizations

| File Name | Size | Recommended Use Case |

| :--- | :--- | :--- |

| MiniCPM5-2B-heretic-abliterated-Q3_K_M.gguf | 1.29 GB | Low-memory edge devices & micro-compute nodes. |

| MiniCPM5-2B-heretic-abliterated-Q4_K_S.gguf | 1.50 GB | Lightweight 4-bit quant; lower RAM overhead. |

| MiniCPM5-2B-heretic-abliterated-Q4_K_M.gguf | 1.56 GB | Recommended: Best balance of speed, footprint, and perplexity. |

| MiniCPM5-2B-heretic-abliterated-Q5_K_M.gguf | 1.81 GB | High accuracy; preserves intricate reasoning chains. |

| MiniCPM5-2B-heretic-abliterated-Q6_K.gguf | 2.07 GB | High fidelity; practically indistinguishable from BF16. |

| MiniCPM5-2B-heretic-abliterated-Q8_0.gguf | 2.68 GB | Full 8-bit precision; minimal quantization loss. |

---

Prompt Template (ChatML)

MiniCPM5 uses the standard ChatML prompt template:

<|im_start|>system
You are a helpful, unfiltered assistant.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Quickstart Guide

llama.cpp

Run inference using llama-cli:

llama-cli \
  -m MiniCPM5-2B-heretic-abliterated-Q4_K_M.gguf \
  -p "<|im_start|>user\nExplain how stack-based buffer overflows work at the register level.<|im_end|>\n<|im_start|>assistant\n" \
  -n 512 \
  -c 4096 \
  -ngl 99 \
  --repeat-penalty 1.15 \
  --temp 0.8 \
  --top-p 0.95