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docs: update README
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<img width="128" height="128" align="right" alt="Logo" src="https://github.com/user-attachments/assets/df5f2840-2f92-4991-aa57-252747d7182e" />
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# Heretic: Fully automatic censorship removal for language models<br><br>[](https://discord.gg/gdXc48gSyT) [](https://huggingface.co/heretic-org)
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# Heretic: Fully automatic censorship removal for language models<br><br>[](https://discord.gg/gdXc48gSyT) [](https://huggingface.co/heretic-org) [](https://codeberg.org/p-e-w/heretic)
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[](https://trendshift.io/repositories/20538)
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@@ -20,6 +20,11 @@ as possible. Using Heretic does not require an understanding of transformer
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internals. In fact, anyone who knows how to run a command-line program
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can use Heretic to decensor language models.
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Heretic supports most dense models, including many multimodal models,
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several different MoE architectures, and even some hybrid models like Qwen3.5.
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Pure state-space models and certain other research architectures are not yet
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supported out of the box.
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<img width="650" height="715" alt="Screenshot" src="https://github.com/user-attachments/assets/d71a5efa-d6be-4705-a817-63332afb2d15" />
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@@ -65,15 +70,15 @@ Heretic have been well-received by users (links and emphasis added):
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> Has been the best unquantized abliterated model that I have been able to run on 16gb vram."
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> [*(Link to comment)*](https://old.reddit.com/r/LocalLLaMA/comments/1phjxca/im_calling_these_people_out_right_now/nt06tji/)
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Heretic supports most dense models, including many multimodal models, and
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several different MoE architectures. It does not yet support SSMs/hybrid models,
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models with inhomogeneous layers, and certain novel attention systems.
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Heretic models have also been independently benchmarked using standard metrics
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like MMLU and GSM8K, and have been found to compare favorably with models
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produced by competing abliteration tools:
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[1](https://old.reddit.com/r/LocalLLaMA/comments/1sojjoc/abliterlitics_benchmark_and_tensor_analysis/),
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[2](https://old.reddit.com/r/LocalLLaMA/comments/1sy18lx/abliterlitics_benchmarks_and_tensor_comparison/).
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You can find a small collection of models that have been decensored using Heretic
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[on Hugging Face](https://huggingface.co/collections/p-e-w/the-bestiary),
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and the community has created and published
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[well over 1,000](https://huggingface.co/models?other=heretic)
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Heretic models in addition to those.
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The community has created and published
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[well over 3000](https://huggingface.co/models?other=heretic)
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models with Heretic.
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## Usage
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@@ -88,6 +93,21 @@ heretic Qwen/Qwen3-4B-Instruct-2507
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Replace `Qwen/Qwen3-4B-Instruct-2507` with whatever model you want to decensor.
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> [!IMPORTANT]
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>
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> While PyTorch 2.2 is the minimum version of PyTorch needed for Heretic to work,
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> some models and configurations might require features only found in
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> later versions. For example, loading MXFP4-quantized models like gpt-oss
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> uses `torch.accelerator`, which was added in PyTorch 2.6.
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> [!TIP]
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>
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> Heretic uses [uv](https://docs.astral.sh/uv/) for dependency management,
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> and the repository includes a `uv.lock` file pinning every package version.
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> If you already use uv (and you probably should!), you can just clone the repo
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> and run Heretic with `uv run heretic`, which ensures that your dependencies
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> match those used by the developers, improving reliability and security.
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The process is fully automatic and does not require configuration; however,
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Heretic has a variety of configuration parameters that can be changed for
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greater control. Run `heretic --help` to see available command-line options,
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@@ -103,7 +123,7 @@ models. Set the `quantization` option to `bnb_4bit` to enable quantization.
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After Heretic has finished decensoring a model, you are given the option to
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save the model, upload it to Hugging Face, chat with it to test how well it works,
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or any combination of those actions.
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run standard benchmarks on it, or any combination of those actions.
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## Research features
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