hotdogs/Agents-A1-4B-kimi-Preview-heretic-GGUF overview

---

license: agpl-3.0

language:

- en

- th

tags:

- agents

- agents-a1

- kimi

- coding

- gguf

- sft

- reasoning

- tool-call

- tool-use

- function-calling

- chatml

- qwen

- preview

- uncensored

- abliterated

- heretic

base_model:

- hotdogs/Agents-A1-4B-kimi-Preview-heretic

datasets:

- greghavens/kimi-k3-coding-and-debugging-traces

library_name: gguf

pipeline_tag: text-generation

---

<h1 align="center">🤖 Agents-A1-4B-kimi-Preview-heretic-GGUF (uncensored)</h1>

<p align="center">

<b>GGUF Quantized — 4B Coding Agent Model · Kimi K3 Traces · Tool-Calling · Unchained 🔓</b>

</p>

<p align="center">

<img src="https://img.shields.io/badge/license-AGPL--3.0-red">

<img src="https://img.shields.io/badge/Base-hotdogs/Agents--A1--4B--kimi--Preview--heretic-blue">

<img src="https://img.shields.io/badge/GGUF-IQ4_NL-brightgreen">

<img src="https://img.shields.io/badge/Uncensored-🔓-red">

<img src="https://img.shields.io/badge/Coding-Agent-orange">

</p>

<br>

> GGUF quantized version of hotdogs/Agents-A1-4B-kimi-Preview-heretic — an abliterated coding agent model with reduced refusal (37%). GGUF format optimized for llama.cpp inference.

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🔓 Uncensored

This GGUF is the quantized version of the heretic-abliterated model. Refusal mechanisms were reduced to ~37% using heretic while preserving coding and reasoning quality.

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✨ Key Features

| Capability | Description |

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

| 🔓 Uncensored | Refusal rate ~37% |

| 💻 Coding Agent | Trained on real Kimi K3 coding traces |

| 🧠 Step-by-step Reasoning | Autonomous agent-style reasoning |

| 🔧 Tool Calling | llama.cpp --tools all support |

| 💬 Multi-turn | 61% multi-turn conversations |

| 🌏 Thai + English | Native bilingual support |

| 🐍 Multi-language | Python, C, C++, Go, Java, Rust, Bash, and more |

| ⚡ Fast Inference | IQ4_NL fits in ~3 GB VRAM |

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📦 Downloads

| File | Size | Description |

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

| Agents-A1-4B-kimi-Preview-heretic-IQ4_NL.gguf | 2.61 GB | Recommended — best quality/speed balance for 8GB VRAM |

| Agents-A1-4B-kimi-Preview-heretic-Q8_0_imatrix.gguf | 4.48 GB | Q8_0 + imatrix — almost lossless |

| Agents-A1-4B-kimi-Preview-heretic-F16.gguf | 8.42 GB | Full BF16 precision |

| imatrix.dat | 3.63 MB | Importance matrix data |

> 🎯 IQ4_NL is recommended for 8GB VRAM users — fits comfortably even at 128K context with flash-attention.

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🚀 Usage

Docker (Recommended)

sudo docker run --rm -p 8080:8080 \
  -v /root/models/:/models \
  --gpus all \
  --ulimit memlock=-1:-1 \
  --env CUDA_VISIBLE_DEVICES=0 \
  ghcr.io/ggml-org/llama.cpp:full-cuda --server \
  -m /models/Agents-A1-4B-kimi-Preview-heretic-IQ4_NL.gguf \
  --host 0.0.0.0 --port 8080 \
  --n-gpu-layers 999 \
  --ctx-size 131072 \
  --batch-size 4096 \
  --ubatch-size 256 \
  --cache-type-k f16 \
  --cache-type-v f16 \
  --flash-attn on \
  --cont-batching \
  --mlock \
  --temp 0.95 \
  --top-k 40 \
  --top-p 0.9 \
  --min-p 0.0 \
  -n -1 \
  --no-mmap \
  --parallel 1 --tools all \
  --dry-multiplier 0.05 \
  --jinja --dry-sequence-breaker none \
  --repeat-penalty 1.1

llama.cpp (Direct)

# Quick test
./llama-cli -m Agents-A1-4B-kimi-Preview-heretic-IQ4_NL.gguf \
  -p "Write a Python function to sort a list" -n 256 --temp 0.6 -ngl 999

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🧬 Model Information

This is a GGUF quantized version of hotdogs/Agents-A1-4B-kimi-Preview-heretic, which is an abliterated fine-tune of InternScience/Agents-A1-4B on coding agent traces.

| Parameter | Value |

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

| Base Model | hotdogs/Agents-A1-4B-kimi-Preview-heretic |

| Parameters | ~4.29B |

| Architecture | Qwen3.5 hybrid (Linear + Full attention) |

| Context | Up to 128K tokens |

| Format | ChatML (Jinja2 template) |

| Fine-tuning | Kimi K3 coding traces (3,389 samples, scale=0.4) |

| Abliteration | heretic — refusal rate ~37% |

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⚠️ Disclaimer

This model is uncensored and may generate content that is offensive, harmful, or inappropriate. Use at your own risk. The authors are not responsible for any misuse.

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🙏 Acknowledgements / ขอบคุณ

• InternScience — For the Agents-A1-4B base model
• greghavens — For the Kimi K3 coding traces dataset
• p-e-w — For the heretic abliteration tool
• Qwen Team (Alibaba) — For the Qwen3.5 architecture
• Unsloth AI — For training optimizations
• All dataset contributors and the open-source AI community ❤️

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💖 Support / โปรดสนับสนุน

If you find this model useful, please consider supporting my work!

หากคุณคิดว่าโมเดลนี้มีประโยชน์ กรุณาสนับสนุนผลงานของฉันด้วยนะคะ! 🙏

<p align="center">

<img src="https://huggingface.co/hotdogs/Qwen35B-Agent-R2/raw/main/donate.webp" alt="Bitcoin QR — Donate" width="256">

</p>

₿ Bitcoin — BTC:

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Thank you for your support! 🙏✨

ขอบคุณมากๆ สำหรับการสนับสนุนค่า! 💖🤗

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