p-e-w/heretic

### Training-free language model modification
Remove censorship, suppress slop, reduce sycophancy, and more.
All in an afternoon, on your gaming PC.
    
   
   
 
    
## Modify any LLM that you can run on your hardware[^1]
[^1]: Heretic supports on-the-fly 4-bit model quantization with bitsandbytes,
which can reduce the amount of VRAM required to process a model to the same amount
that is used to run a typical quantized version of it, at a slight accuracy cost.
Set the quantization option to bnb4bit to enable this.
Heretic is a unique tool that lets you do what only corporations with access
to massive computing power usually do: Modify, rather than merely run,
language models. It does not perform expensive training; rather, it uses
a collection of mathematical techniques to steer behavior based on contrasting
example prompts and matching scorers.
Heretic can, depending on the configuration:
Suppress refusals/remove censorship (this is the default action)
Reduce slop (config.noslop.toml)
Reduce humor (config.nohumor.toml)
Reduce sycophancy (config.nosyco.toml)
Alter emotional alignment (config.emotions.toml)
and many, many other things.
### :bangbang: Using Heretic does NOT require understanding how language models work internally :bangbang:
In fact, you can go from zero to removing censorship from your first model
in a matter of seconds. Heretic supports most dense models, including
many multimodal models, several different MoE architectures, and many modern
hybrid models.
The community has created and published
thousands
of models with Heretic.
Heretic models have been independently benchmarked using standard metrics
like MMLU and GSM8K, and have been found to compare favorably against models
produced with competing abliteration tools.[^2][^3]
[^2]: https://old.reddit.com/r/LocalLLaMA/comments/1sojjoc/abliterliticsbenchmarkandtensoranalysis/
[^3]: https://old.reddit.com/r/LocalLLaMA/comments/1sy18lx/abliterliticsbenchmarksandtensorcomparison/
 
 
## Usage
Prepare a Python 3.10+ environment with PyTorch 2.6+ installed as appropriate
for your hardware. Then run:
sh
pip install -U heretic-llm
heretic Qwen/Qwen3-4B-Instruct-2507
Replace Qwen/Qwen3-4B-Instruct-2507 with whatever model you want to process.
By default, Heretic performs censorship removal (refusal suppression).
If you want to do something else, choose one of the configuration files linked
above, or write your own. See config.default.toml
for available configuration options.
> [!IMPORTANT]
> Configuration files made for Heretic 1.x are not compatible with Heretic 2.x!
> See the migration guide for what you need to change
> in order to make your old configurations work.
At the start of a program run, Heretic benchmarks the system to determine
the optimal batch size to make the most of the available hardware.
On an RTX 3090, with the default configuration, processing
Qwen3-4B-Instruct-2507
takes about 30-40 minutes.
After Heretic has finished processing a model, you are given the choice to
save the model, upload it to Hugging Face, chat with it to test how well it works,
run standard benchmarks on it, or any combination of those actions.