Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-MTP

Customize or build on this model

Listed from public GitHub data, not tested by us. Read the code and license before you run anything.

Linked in the model card

GitHub repositories the original model card links to.

• p-e-w/heretic ↗

  Repo’s own description: Fully automatic censorship removal for language models

  ★ 36,421 · Last updated 2026-10-24 · License: AGPL-3.0

• sgl-project/sglang ↗

  Repo’s own description: SGLang is a high-performance serving framework for large language models and multimodal models.

  ★ 38,005 · Last updated 2026-10-25 · License: Apache-2.0

• vllm-project/vllm ↗

  Repo’s own description: A high-throughput and memory-efficient inference and serving engine for LLMs

  ★ 95,376 · Last updated 2026-10-25 · License: Apache-2.0

• kvcache-ai/ktransformers ↗

  Repo’s own description: A Flexible Framework for Experiencing Heterogeneous LLM Inference/Fine-tune Optimizations

  ★ 19,630 · Last updated 2026-10-20 · License: Apache-2.0

• QwenLM/Qwen-Agent ↗

  Repo’s own description: Agent framework and applications built upon Qwen>=3.0, featuring Function Calling, MCP, Code Interpreter, RAG, Chrome extension, etc.

  ★ 17,211 · Last updated 2026-03-04 · License: Apache-2.0

• QwenLM/qwen-code ↗

  Repo’s own description: An open-source AI coding agent that lives in your terminal.

  ★ 28,707 · Last updated 2026-10-25 · License: Apache-2.0

Tools to customize it further

Remove more refusals

• OBLITERATUS ↗ ★ 8,946

  A larger refusal-removal toolkit with several abliteration methods, usable locally or through a hosted Hugging Face Space. Check the telemetry setting before you run it: the README describes telemetry as opt-in, but on by default in the Spaces version.

• remove-refusals-with-transformers ↗ ★ 2,312

  A small proof-of-concept that computes a refusal direction and removes it using plain Hugging Face Transformers instead of TransformerLens. The author says it was mostly tested on models under 3B and that some custom architectures, including some Qwen implementations, may not work.

Fine-tune it on your own data

• Unsloth ↗ ★ 78,528

  A desktop app and Python library for running and training models locally. Its README lists LoRA, QLoRA, full fine-tuning, DPO and GRPO, plus export to formats including GGUF, on Windows, Linux, WSL and macOS.

• LlamaFactory ↗ ★ 75,713

  Fine-tunes more than 100 language and vision-language models from a command line or a browser-based Web UI, aimed at training without writing code.

Make a smaller download (quantize)

• llama.cpp ↗ ★ 132,260

  Runs models locally and includes the tools behind most GGUF files. A conversion script turns Hugging Face weights into GGUF, and llama-quantize shrinks a high-precision GGUF to lower-bit formats, which can cost some accuracy.

• MLX LM ↗ ★ 7,467

  Apple's MLX package for running and fine-tuning models on Apple silicon. It can quantize models and upload them to the Hugging Face Hub, and supports LoRA and full fine-tuning.

Merge it with another model

• mergekit ↗ ★ 7,414

  Merges pretrained models with many merge methods. It works out-of-core, so merges can run on a CPU or with as little as 8 GB of VRAM, and it also handles LoRA extraction and mixture-of-experts merges.

Learn the techniques

• LLM Course ↗ ★ 84,667

  A free course with roadmaps and Colab notebooks. Its notebooks include one-click tools for merging with MergeKit, quantizing to GGUF, GPTQ, EXL2, AWQ and HQQ, and automatic abliteration with custom datasets.

Compare all tools →