Any-to-Any
Transformers
Safetensors
gemma4
image-text-to-text
heretic
uncensored
decensored
abliterated
reproducible
Instructions to use p-e-w/gemma-4-E4B-it-heretic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use p-e-w/gemma-4-E4B-it-heretic with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("p-e-w/gemma-4-E4B-it-heretic") model = AutoModelForMultimodalLM.from_pretrained("p-e-w/gemma-4-E4B-it-heretic") - Notebooks
- Google Colab
- Kaggle
| # Reproduction guide | |
| This directory contains the necessary information and assets to reproduce the results obtained during this Heretic run. | |
| > [!WARNING] | |
| > **Local code** | |
| > | |
| > This system installed Heretic from a local directory or wheel. Uncommitted or experimental code may have been executed. | |
| > | |
| > Reproducibility *cannot* be guaranteed in this environment. | |
| ## Models | |
| - **Base model:** [google/gemma-4-E4B-it](https://huggingface.co/google/gemma-4-E4B-it) (Commit: [`fee6332`](https://huggingface.co/google/gemma-4-E4B-it/commit/fee6332c1abaafb77f6f9624236c63aa2f1d0187)) | |
| ## Datasets | |
| - **Good prompts:** [mlabonne/harmless_alpaca](https://huggingface.co/datasets/mlabonne/harmless_alpaca) (Commit: [`02c6a92`](https://huggingface.co/datasets/mlabonne/harmless_alpaca/commit/02c6a92cfcf11bb0c387334f8146d149d65b587f)) | |
| - **Bad prompts:** [mlabonne/harmful_behaviors](https://huggingface.co/datasets/mlabonne/harmful_behaviors) (Commit: [`01cead0`](https://huggingface.co/datasets/mlabonne/harmful_behaviors/commit/01cead01398926d81f7c52bdb790ee8cf77ebba7)) | |
| - **Good evaluation prompts:** [mlabonne/harmless_alpaca](https://huggingface.co/datasets/mlabonne/harmless_alpaca) (Commit: [`02c6a92`](https://huggingface.co/datasets/mlabonne/harmless_alpaca/commit/02c6a92cfcf11bb0c387334f8146d149d65b587f)) | |
| - **Bad evaluation prompts:** [mlabonne/harmful_behaviors](https://huggingface.co/datasets/mlabonne/harmful_behaviors) (Commit: [`01cead0`](https://huggingface.co/datasets/mlabonne/harmful_behaviors/commit/01cead01398926d81f7c52bdb790ee8cf77ebba7)) | |
| ## Selected trial | |
| - **Trial number:** 88 | |
| - **KL divergence:** 0.007246 | |
| - **Refusals:** 42/100 | |
| ## System | |
| - **Python:** 3.12.3 (CPython, GCC 13.3.0) [System] | |
| - **Operating system:** Linux-6.8.0-111-generic-x86_64-with-glibc2.39 (x86_64) | |
| - **CPU:** AMD EPYC 7713P 64-Core Processor | |
| ### Accelerators | |
| - **CUDA:** Detected 1 device(s) (31.37 GB total VRAM) | |
| - **CUDA Version:** 12.8 | |
| - **Driver Version:** 580.159.03 | |
| - **Devices:** | |
| - **CUDA 0:** NVIDIA RTX PRO 4500 Blackwell (31.37 GB) | |
| ## Environment | |
| - **Heretic:** v1.3.0 (Origin: Local) | |
| - **PyTorch:** 2.8.0+cu128 | |
| - **Other dependencies:** See [`requirements.txt`](requirements.txt). | |
| ## Contents of this directory | |
| - [`requirements.txt`](requirements.txt): The exact versions of all Python packages. | |
| - [`config.toml`](config.toml): The exact configuration used, including the RNG seed. | |
| - [`google--gemma-4-E4B-it.jsonl`](google--gemma-4-E4B-it.jsonl): The Optuna study journal containing the history of all trials. | |
| - [`SHA256SUMS`](SHA256SUMS): Cryptographic hashes for all weight files. | |
| - [`reproduce.json`](reproduce.json): A machine-readable file containing all reproducibility information. | |
| ## How to reproduce | |
| 1. Ensure your system matches the specifications in the **System** section above. Exact reproducibility is only guaranteed if all aspects of your system are identical to the one the model was originally generated on. | |
| 1. Install the exact version of Heretic indicated in the **Environment** section above, from its original source. | |
| 1. Install the packages listed in `requirements.txt`: `pip install -r requirements.txt` | |
| 1. Install the correct version of PyTorch: `pip install torch==2.8.0+cu128 --index-url https://download.pytorch.org/whl/cu128` | |
| 1. Place the provided `config.toml` in your working directory. | |
| 1. Run Heretic without any additional arguments: `heretic` | |
| 1. Wait for the run to finish, then select trial **88** and export the model. | |
| 1. Verify that the weight files have been exactly reproduced by comparing their SHA-256 hashes against those in `SHA256SUMS`: `sha256sum -c SHA256SUMS` (or look at the hashes online if you uploaded to Hugging Face) | |
| > [!TIP] | |
| > To use the included Optuna study journal `google--gemma-4-E4B-it.jsonl`, place it in the checkpoints directory (usually `checkpoints/`) before running Heretic. | |
| > | |
| > This allows you to export other models from the Pareto front, or to run additional trials without having to re-run the stored trials. | |