diff --git a/README.md b/README.md index a444e60..95801e2 100644 --- a/README.md +++ b/README.md @@ -1,89 +1,79 @@ -Logo +
-# Heretic: Fully automatic censorship removal for language models

[![Discord](https://img.shields.io/discord/1447831134212984903?color=5865F2&label=discord&labelColor=black&logo=discord&logoColor=white&style=for-the-badge)](https://discord.gg/gdXc48gSyT) [![Matrix](https://img.shields.io/badge/Matrix-black?logo=matrix&style=for-the-badge)](https://matrix.to/#/#heretic:matrix.org) [![Follow us on Hugging Face](https://huggingface.co/datasets/huggingface/badges/resolve/main/follow-us-on-hf-md-dark.svg)](https://huggingface.co/heretic-org) [![Codeberg mirror](https://img.shields.io/badge/Codeberg%20mirror-black?logo=codeberg&style=for-the-badge)](https://codeberg.org/p-e-w/heretic) +Heretic logo -[![#1 Repository of the Day](https://trendshift.io/api/badge/repositories/20538)](https://trendshift.io/repositories/20538) +# Heretic -Heretic is a tool that removes censorship (aka "safety alignment") from -transformer-based language models without expensive post-training. -It combines an advanced implementation of directional ablation, also known -as "abliteration" ([Arditi et al. 2024](https://arxiv.org/abs/2406.11717), -Lai 2025 ([1](https://huggingface.co/blog/grimjim/projected-abliteration), -[2](https://huggingface.co/blog/grimjim/norm-preserving-biprojected-abliteration))), -with a TPE-based parameter optimizer powered by [Optuna](https://optuna.org/). +### Training-free language model modification -This approach enables Heretic to work **completely automatically.** Heretic -finds high-quality abliteration parameters by co-minimizing the number of -refusals and the KL divergence from the original model. This results in a -decensored model that retains as much of the original model's intelligence -as possible. Using Heretic does not require an understanding of transformer -internals. In fact, anyone who knows how to run a command-line program -can use Heretic to decensor language models. +**Remove censorship**, suppress slop, reduce sycophancy, and more.
+All in an afternoon, on your gaming PC. -Heretic supports most dense models, including many multimodal models, -several different MoE architectures, and even some hybrid models like Qwen3.5. -Pure state-space models and certain other research architectures are not yet -supported out of the box. +[![Discord](https://img.shields.io/discord/1447831134212984903?color=5865F2&label=discord&labelColor=black&logo=discord&logoColor=white&style=for-the-badge)](https://discord.gg/gdXc48gSyT)     +[![Matrix](https://img.shields.io/badge/Matrix-black?logo=matrix&style=for-the-badge)](https://matrix.to/#/#heretic:matrix.org)    +[![Follow us on Hugging Face](https://huggingface.co/datasets/huggingface/badges/resolve/main/follow-us-on-hf-md-dark.svg)](https://huggingface.co/heretic-org)    +[![Codeberg mirror](https://img.shields.io/badge/Codeberg%20mirror-black?logo=codeberg&style=for-the-badge)](https://codeberg.org/p-e-w/heretic) -Screenshot +
+ +-----   -Running unsupervised with the default configuration, Heretic can produce -decensored models that rival the quality of abliterations created manually -by human experts: +[![#1 Repository of the Day](https://trendshift.io/api/badge/repositories/20538)](https://trendshift.io/repositories/20538)     +[![Model and download statistics](https://github.com/user-attachments/assets/c9b5a660-7ef9-43c7-991c-fd9d63ea8bd8)](https://heretic.sdad.pro/) -| Model | Refusals for "harmful" prompts | KL divergence from original model for "harmless" prompts | -| :--- | ---: | ---: | -| [google/gemma-3-12b-it](https://huggingface.co/google/gemma-3-12b-it) (original) | 97/100 | 0 *(by definition)* | -| [mlabonne/gemma-3-12b-it-abliterated-v2](https://huggingface.co/mlabonne/gemma-3-12b-it-abliterated-v2) | 3/100 | 1.04 | -| [huihui-ai/gemma-3-12b-it-abliterated](https://huggingface.co/huihui-ai/gemma-3-12b-it-abliterated) | 3/100 | 0.45 | -| **[p-e-w/gemma-3-12b-it-heretic](https://huggingface.co/p-e-w/gemma-3-12b-it-heretic) (ours)** | **3/100** | **0.16** | -The Heretic version, generated without any human effort, achieves the same -level of refusal suppression as other abliterations, but at a much lower -KL divergence, indicating less damage to the original model's capabilities. -*(You can reproduce those numbers using Heretic's built-in evaluation functionality, -e.g. `heretic --model google/gemma-3-12b-it --evaluate-model p-e-w/gemma-3-12b-it-heretic`. -Note that the exact values might be platform- and hardware-dependent. -The table above was compiled using PyTorch 2.8 on an RTX 5090.)* +## Modify any LLM that you can run on your hardware[^1] -Of course, mathematical metrics and automated benchmarks never tell the whole -story, and are no substitute for human evaluation. Models generated with -Heretic have been well-received by users (links and emphasis added): +[^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 `bnb_4bit` to enable this. -> "I was skeptical before, but I just downloaded -> [**GPT-OSS 20B Heretic**](https://huggingface.co/p-e-w/gpt-oss-20b-heretic) -> model and holy shit. It gives properly formatted long responses to sensitive topics, -> using the exact uncensored words that you would expect from an uncensored model, -> produces markdown format tables with details and whatnot. Looks like this is -> the best abliterated version of this model so far..." -> [*(Link to comment)*](https://old.reddit.com/r/LocalLLaMA/comments/1oymku1/heretic_fully_automatic_censorship_removal_for/np6tba6/) +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 GPT 20b**](https://huggingface.co/p-e-w/gpt-oss-20b-heretic) -> seems to be the best uncensored model I have tried yet. It doesn't destroy a -> the model's intelligence and it is answering prompts normally would be -> rejected by the base model." -> [*(Link to comment)*](https://old.reddit.com/r/LocalLLaMA/comments/1oymku1/heretic_fully_automatic_censorship_removal_for/npe9jng/) +Heretic can, depending on the configuration: -> "[[**Qwen3-4B-Instruct-2507-heretic**](https://huggingface.co/p-e-w/Qwen3-4B-Instruct-2507-heretic)] -> Has been the best unquantized abliterated model that I have been able to run on 16gb vram." -> [*(Link to comment)*](https://old.reddit.com/r/LocalLLaMA/comments/1phjxca/im_calling_these_people_out_right_now/nt06tji/) +* **Suppress refusals/remove censorship** (this is the [default action](/config.default.toml)) +* Reduce slop ([`config.noslop.toml`](/config.noslop.toml)) +* Reduce humor ([`config.nohumor.toml`](/config.nohumor.toml)) +* Reduce sycophancy ([`config.nosyco.toml`](/config.nosyco.toml)) +* Alter emotional alignment ([`config.emotions.toml`](/config.emotions.toml)) -Heretic models have also been independently benchmarked using standard metrics -like MMLU and GSM8K, and have been found to compare favorably with models -produced by competing abliteration tools: -[1](https://old.reddit.com/r/LocalLLaMA/comments/1sojjoc/abliterlitics_benchmark_and_tensor_analysis/), -[2](https://old.reddit.com/r/LocalLLaMA/comments/1sy18lx/abliterlitics_benchmarks_and_tensor_comparison/). +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](#usage). Heretic supports most dense models, including +many multimodal models, several different MoE architectures, and many modern +hybrid models. The community has created and published -[well over 5000](https://huggingface.co/models?other=heretic) -models with Heretic. +[thousands](https://huggingface.co/models?other=heretic) +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/abliterlitics_benchmark_and_tensor_analysis/ +[^3]: https://old.reddit.com/r/LocalLLaMA/comments/1sy18lx/abliterlitics_benchmarks_and_tensor_comparison/ + +  + +Heretic screenshot + +  ## Usage -Prepare a Python 3.10+ environment with PyTorch 2.2+ installed as appropriate +Prepare a Python 3.10+ environment with PyTorch 2.6+ installed as appropriate for your hardware. Then run: ```sh @@ -91,87 +81,176 @@ pip install -U heretic-llm heretic Qwen/Qwen3-4B-Instruct-2507 ``` -Replace `Qwen/Qwen3-4B-Instruct-2507` with whatever model you want to decensor. +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`](/config.default.toml) +for available configuration options. > [!IMPORTANT] > -> While PyTorch 2.2 is the minimum version of PyTorch needed for Heretic to work, -> some models and configurations might require features only found in -> later versions. For example, loading MXFP4-quantized models like gpt-oss -> uses `torch.accelerator`, which was added in PyTorch 2.6. - -> [!TIP] -> -> Heretic uses [uv](https://docs.astral.sh/uv/) for dependency management, -> and the repository includes a `uv.lock` file pinning every package version. -> If you already use uv (and you probably should!), you can just clone the repo -> and run Heretic with `uv run heretic`, which ensures that your dependencies -> match those used by the developers, improving reliability and security. - -The process is fully automatic and does not require configuration; however, -Heretic has a variety of configuration parameters that can be changed for -greater control. Run `heretic --help` to see available command-line options, -or look at [`config.default.toml`](config.default.toml) if you prefer to use -a configuration file. +> Configuration files made for Heretic 1.x are **not** compatible with Heretic 2.x! +> See the [migration guide](/docs/migration_v1_to_v2.md) 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, decensoring +On an RTX 3090, with the default configuration, processing [Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507) -takes about 20-30 minutes. Note that Heretic supports model quantization with -bitsandbytes, which can drastically reduce the amount of VRAM required to process -models. Set the `quantization` option to `bnb_4bit` to enable quantization. +takes about 30-40 minutes. -After Heretic has finished decensoring a model, you are given the option to +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. +## Controlling what Heretic does using scorer plugins + +Heretic steers model behavior by optimizing one or multiple scores. Scores are +computed by scorer plugins. You can easily write your own scorers to get full +control over what Heretic does to models. + +The `Scorer` interface (abstract base class) your scorer needs to inherit from +is defined in [`scorer.py`](/src/heretic/scorer.py). The only required method +is `get_score`, but there is more machinery (such as settings management) +available when you need it. + +By default, Heretic scores models by refusal rate (implemented in +[`keyword_rate.py`](/src/heretic/scorers/keyword_rate.py)) and KL divergence +(implemented in [`kl_divergence.py`](/src/heretic/scorers/kl_divergence.py)). +Additional scorers are available in the [`scorers` directory](/src/heretic/scorers/). +These scorers can serve as examples for your own implementations, and can easily +be adapted to your needs. + +Scorers are configured through the [main configuration file](/config.default.toml). +Which scorer plugins are active is determined by the `scorers` setting, which +also controls whether a scorer's score should be minimized or maximized during +optimization. Any number of scorers can be used simultaneously, and their scores +will be co-optimized. Multiple instances of the same scorer can be configured +with different settings. See the configuration file for the full documentation +of this mechanism. + +The path to a scorer plugin can be specified either as a fully qualified import +path (`fully.qualified.module.MyScorerClass`) or as a file path followed by +a class name (`path/to/plugin.py:MyScorerClass`). You do **not** have to modify +the Heretic package code in order to use your own plugins. + +Heretic also has modifier plugins, which are described in +[the next section](#how-heretic-works). + + ## How Heretic works -Heretic implements a parametrized variant of directional ablation. For each -supported transformer component (currently, attention out-projection and -MLP down-projection), it identifies the associated matrices in each transformer -layer, and orthogonalizes them with respect to the relevant "residual direction", -inhibiting the expression of that direction in the result of multiplications -with that matrix. +Heretic combines a pluggable modifier (interface in +[`modifier.py`](/src/heretic/modifier.py)) with a TPE-based hyperparameter optimizer +powered by [Optuna](https://optuna.org/). The optimizer finds a set of parameters that, +when passed to the modifier, minimize or maximize a set of configurable scores on the resulting model ([see above](#controlling-what-heretic-does-using-scorer-plugins)). -Residual directions are computed for each layer as a difference-of-means between -the first-token residuals for "harmful" and "harmless" example prompts. +Heretic ships with two modifiers: -The ablation process is controlled by several optimizable parameters: +* **Arbitrary-Rank Ablation (ARA)**[^4]: This is the default modifier, and was + specifically developed for use in Heretic. You can find an overview of how ARA + works in [the original pull request](https://github.com/p-e-w/heretic/pull/211), + and see the precise implementation in [`ara.py`](/src/heretic/modifiers/ara.py). -* `direction_index`: Either the index of a residual direction, or the special - value `per layer`, indicating that each layer should be ablated using the - residual direction associated with that layer. -* `max_weight`, `max_weight_position`, `min_weight`, and `min_weight_distance`: - For each component, these parameters describe the shape and position of the - ablation weight kernel over the layers. The following diagram illustrates this: +* **Directional ablation aka "abliteration"**[^5]: The classic method for refusal + suppression. Heretic's implementation uses a flexible ablation weight kernel over + the layers, and supports both projected abliteration[^6] and norm preservation (MPOA)[^7]. + The complete code is in [`abliteration.py`](/src/heretic/modifiers/abliteration.py). -Explanation +[^4]: *Weidmann 2026.* A preprint explaining the technique will be available soon. +[^5]: *[Arditi et al. 2024](https://arxiv.org/abs/2406.11717)* +[^6]: *[Lai 2025 (1)](https://huggingface.co/blog/grimjim/projected-abliteration)* +[^7]: *[Lai 2025 (2)](https://huggingface.co/blog/grimjim/norm-preserving-biprojected-abliteration)* -  +You can use the `modifiers` setting to switch between modifier implementations. +Despite the name of the setting using a plural form, Heretic currently allows +only a single modifier for a given processing run. This may change in the future. -Heretic's main innovations over existing abliteration systems are: -* The shape of the ablation weight kernel is highly flexible, which, combined with - automatic parameter optimization, can improve the compliance/quality tradeoff. - Non-constant ablation weights were previously explored by Maxime Labonne in - [gemma-3-12b-it-abliterated-v2](https://huggingface.co/mlabonne/gemma-3-12b-it-abliterated-v2). -* The residual direction index is a float rather than an integer. For non-integral - values, the two nearest residual direction vectors are linearly interpolated. - This unlocks a vast space of additional directions beyond the ones identified - by the difference-of-means computation, and often enables the optimization - process to find a better direction than that belonging to any individual layer. -* Ablation parameters are chosen separately for each component. I have found that - MLP interventions tend to be more damaging to the model than attention interventions, - so using different ablation weights can squeeze out some extra performance. +## Reproducibility and the Heretic Grimoire + +Heretic has the ability to create *reproducible models* whose repositories contain +all information required to produce a byte-for-byte identical model on demand, +provided that the environment is perfectly identical to the original one. PyTorch +doesn't guarantee that operations return identical outputs unless hardware, drivers, +operating system, and the entire software stack including all package versions +are exactly the same. + +Heretic manages all that complexity for you. When uploading a processed model to +Hugging Face, Heretic offers to include reproducibility information. This is entirely +optional, but if you choose to do so, the uploaded repository will contain a +`reproduce` folder with detailed instructions for recreating the model +([example](https://huggingface.co/heretic-org/LFM2.5-VL-3B-heretic/tree/main/reproduce)). +This folder contains both human-readable instructions and a machine-readable manifest +file named `reproduce.json`, which includes all the information Heretic needs to +**automatically** reproduce the model. + +Automatic reproduction can be performed with + +```sh +heretic --reproduce path/to/reproduce.json +``` + +Heretic will guide you through the process, checking your environment against the one +that was used to create the model, and pointing out potentially problematic mismatches. +The multi-hour computations that were required to make the original model do **not** +have to be re-done, and the entire process typically takes a few minutes. After you +have exported the resulting model, Heretic will verify the hashes of the weight files +against those stored in the reproduction manifest (they may or may not be identical, +depending on how closely your system resembles the original one). + +Many people have uploaded models with reproducibility information to Hugging Face. +Since a reproduction manifest is only around 9 kilobytes in size, these manifests +form a portable library of models that can be reproduced at will. + +### That library is called the Heretic Grimoire. You can view it [here](https://huggingface.co/spaces/heretic-org/Heretic-Grimoire). + +But you don't have to rely on an externally hosted web application to access the +library of manifests: The Grimoire is fundamentally designed as a *distributed* system, +and you can fetch your own local copies of publicly available manifests from +Hugging Face whenever you want by running + +```sh +heretic --collect-reproducibles path/to/target/folder/ +``` + +You now have a local backup of all reproducible Heretic models, properly catalogued. +To update this collection, simply run the command again. It functions as an +append-only backup, never deleting files even if the corresponding model no longer +exists on Hugging Face. + + +## Heretic is made by humans! + +Unlike lots of AI-related software today (and indeed lots of software in general), +Heretic is **not** "vibe-coded". + +All of [my](https://github.com/p-e-w) commits in this project so far were written +100% by hand, the way I have been doing programming for decades, and while some +Heretic contributors use coding agents, I review every single line of code that I +merge very carefully. There's no "LGTM" here! + +Don't believe me? Check out [this pull request](https://github.com/p-e-w/heretic/pull/53), +which accumulated **almost 350 human-written comments** over more than 7 months +as we discussed the implementation. +And [here is another PR](https://github.com/p-e-w/heretic/pull/191) with +**more than 200 comments.** + +I am the opposite of a luddite and I have used agents for other projects, but +I am proud of the code I write and so far can't quite bring myself to let a machine +write it for me in a project I care so much about. As a result, Heretic has a lean, +relatively simple codebase that in my opinion, and in that of some others, +is a pleasure to work on. + +If you like that, join us! Hop on the Discord and tell us about your ideas for +improvements, or directly file an issue or open a PR. ## Prior art -I'm aware of the following publicly available implementations of abliteration -techniques: +I'm aware of the following implementations of abliteration techniques +that were publicly available when Heretic was first released (November 2025): * [AutoAbliteration](https://huggingface.co/posts/mlabonne/714992455492422) * [abliterator.py](https://github.com/FailSpy/abliterator) @@ -188,11 +267,13 @@ any of those projects. The development of Heretic was informed by: -* [The original abliteration paper (Arditi et al. 2024)](https://arxiv.org/abs/2406.11717) +* [The original abliteration paper *(Arditi et al. 2024)*](https://arxiv.org/abs/2406.11717) * [Maxime Labonne's article on abliteration](https://huggingface.co/blog/mlabonne/abliteration), - as well as some details from the model cards of his own abliterated models (see above) + as well as some details from the model cards of his own abliterated models, such as + the use of non-constant ablation weights * Jim Lai's articles describing ["projected abliteration"](https://huggingface.co/blog/grimjim/projected-abliteration) and ["norm-preserving biprojected abliteration"](https://huggingface.co/blog/grimjim/norm-preserving-biprojected-abliteration) +* Thousands of interactions with members of the community ## Citation @@ -202,7 +283,7 @@ If you use Heretic for your research, please cite it using the following BibTeX ```bibtex @misc{heretic, author = {Weidmann, Philipp Emanuel}, - title = {Heretic: Fully automatic censorship removal for language models}, + title = {Heretic: Training-free language model modification}, year = {2025}, publisher = {GitHub}, journal = {GitHub repository}, @@ -230,3 +311,10 @@ along with this program. If not, see . **By contributing to this project, you agree to release your contributions under the same license.** + + +  + +  + +  diff --git a/docs/migration_v1_to_v2.md b/docs/migration_v1_to_v2.md new file mode 100644 index 0000000..b793729 --- /dev/null +++ b/docs/migration_v1_to_v2.md @@ -0,0 +1,67 @@ +# Migrating from Heretic 1.x to Heretic 2.x + +Heretic 2.x is not backwards compatible with Heretic 1.x configurations. + +If you have existing configuration files written to work with a Heretic 1.x release, +you need to make the following changes before using them with a Heretic 2.x release. +Only settings that are actually in your configuration file must be updated; +defaults are automatically set to the current values. Of course, you can also simply +start with [an up-to-date default configuration](/config.default.toml), and modify +it to match your requirements. + + +## Remove settings for research features + +Research features have been removed in Heretic 2.0. The following settings +are no longer recognized: + +* `print_residual_geometry` +* `plot_residuals` +* `residual_plot_path` +* `residual_plot_title` +* `residual_plot_style` +* `residual_plot_label` and `residual_plot_color` in prompt sections + + +## Remove `kl_divergence_scale` and `kl_divergence_target` + +KL divergence balancing has been removed and these settings +are no longer recognized. + + +## Rename `chain_of_thought_skips` to `chain_of_thought_blocks` and update its structure + +The new setting `chain_of_thought_blocks` contains pairs of the form +`[cot_initializer, cot_finalizer]` instead of `[cot_initializer, closed_cot_block]`. + + +## Move abliteration settings to the `[modifier.Abliteration]` section + +This includes the following settings: + +* `orthogonalize_direction` +* `row_normalization` +* `full_normalization_lora_rank` +* `winsorization_quantile` +* `[good_prompts]` (renamed to `[modifier.Abliteration.good_prompts]`) +* `[bad_prompts]` (renamed to `[modifier.Abliteration.bad_prompts]`) + +> [!IMPORTANT] +> +> Heretic 2.x defaults to using ARA for modifying models, not abliteration. +> To continue using abliteration, edit the `modifiers` setting accordingly. +> To configure ARA, edit the `[modifier.ARA]` section. + + +## Move refusal evaluation settings to the `[scorer.KeywordRate]` section + +This includes the following settings: + +* `print_responses` +* `refusal_markers` (renamed to `keyword_markers`) +* `[bad_evaluation_prompts]` (renamed to `[scorer.KeywordRate.prompts]`) + + +## Rename `[good_evaluation_prompts]` to `[scorer.KLDivergence.prompts]` + +KL divergence is now computed by a scorer plugin. diff --git a/pyproject.toml b/pyproject.toml index 83b5a7d..073e64a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,7 +1,7 @@ [project] name = "heretic-llm" -version = "2.0.0.dev0" -description = "Fully automatic censorship removal for language models" +version = "2.0.0" +description = "Training-free language model modification" readme = "README.md" license = "AGPL-3.0-or-later" authors = [ @@ -10,7 +10,7 @@ authors = [ requires-python = ">=3.10" keywords = ["llm", "transformer", "abliteration"] classifiers = [ - "Development Status :: 4 - Beta", + "Development Status :: 5 - Production/Stable", "Environment :: Console", "Environment :: GPU", "Intended Audience :: Science/Research", @@ -19,6 +19,9 @@ classifiers = [ "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.12", + "Programming Language :: Python :: 3.13", + "Programming Language :: Python :: 3.14", + "Programming Language :: Python :: 3.15", ] dependencies = [ "accelerate~=1.15", @@ -72,8 +75,7 @@ ignore = [ ] [tool.uv] -# TODO: Re-enable before 2.0 release! -#exclude-newer = "7 days" +exclude-newer = "7 days" [tool.uv.sources] torch = { index = "pytorch" } diff --git a/uv.lock b/uv.lock index 290853a..7b213b3 100644 --- a/uv.lock +++ b/uv.lock @@ -18,6 +18,10 @@ resolution-markers = [ "python_full_version < '3.11' and sys_platform == 'darwin'", ] +[options] +exclude-newer = "0001-01-01T00:00:00Z" # This has no effect and is included for backwards compatibility when using relative exclude-newer values. +exclude-newer-span = "P7D" + [[package]] name = "absl-py" version = "2.5.0" @@ -1078,7 +1082,7 @@ wheels = [ [[package]] name = "heretic-llm" -version = "2.0.0.dev0" +version = "2.0.0" source = { editable = "." } dependencies = [ { name = "accelerate" },