71 lines
4.1 KiB
Markdown
71 lines
4.1 KiB
Markdown
# Reproduction guide
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This directory contains the necessary information and assets to reproduce the results obtained during this Heretic run.
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## Models
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- **Base model:** [adamm-hf/Hypnos-i1-8B](https://huggingface.co/adamm-hf/Hypnos-i1-8B) (Commit: [`efc4ca0`](https://huggingface.co/adamm-hf/Hypnos-i1-8B/commit/efc4ca0bb8a56f41493a6c24095ecd83e7972fc5))
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## Datasets
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- **Good prompts:** [mlabonne/harmless_alpaca](https://huggingface.co/datasets/mlabonne/harmless_alpaca) (Commit: [`02c6a92`](https://huggingface.co/datasets/mlabonne/harmless_alpaca/commit/02c6a92cfcf11bb0c387334f8146d149d65b587f))
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- **Bad prompts:** [mlabonne/harmful_behaviors](https://huggingface.co/datasets/mlabonne/harmful_behaviors) (Commit: [`01cead0`](https://huggingface.co/datasets/mlabonne/harmful_behaviors/commit/01cead01398926d81f7c52bdb790ee8cf77ebba7))
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- **Good evaluation prompts:** [mlabonne/harmless_alpaca](https://huggingface.co/datasets/mlabonne/harmless_alpaca) (Commit: [`02c6a92`](https://huggingface.co/datasets/mlabonne/harmless_alpaca/commit/02c6a92cfcf11bb0c387334f8146d149d65b587f))
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- **Bad evaluation prompts:** [mlabonne/harmful_behaviors](https://huggingface.co/datasets/mlabonne/harmful_behaviors) (Commit: [`01cead0`](https://huggingface.co/datasets/mlabonne/harmful_behaviors/commit/01cead01398926d81f7c52bdb790ee8cf77ebba7))
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## Selected trial
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- **Trial number:** 169
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- **KL divergence:** 0.043065
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- **Refusals:** 3/100
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## System
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- **Python:** 3.12.3 (CPython, GCC 13.3.0) [Virtualenv/Venv]
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- **Operating system:** Linux-6.17.0-35-generic-x86_64-with-glibc2.39 (x86_64)
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- **CPU:** AMD Ryzen 9 9950X3D 16-Core Processor
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### Accelerators
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- **ROCm:** Detected 2 device(s) (63.72 GB total VRAM)
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- **HIP Version:** 7.2.53211
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- **Driver Version:** AMDSMI Tool: 26.2.2+c2d9476115 | AMDSMI Library version: 26.2.2 | ROCm version: 7.2.3 | amdgpu version: 6.16.13 | hsmp version: N/A
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- **Devices:**
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- **ROCm 0:** AMD Radeon AI PRO R9700 (31.86 GB)
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- **ROCm 1:** AMD Radeon AI PRO R9700 (31.86 GB)
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## Environment
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- **Heretic:** v1.4.0 (Origin: PyPI)
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- **PyTorch:** 2.12.0+rocm7.2
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- **Other dependencies:** See [`requirements.txt`](requirements.txt).
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## Contents of this directory
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- [`requirements.txt`](requirements.txt): The exact versions of all Python packages.
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- [`config.toml`](config.toml): The exact configuration used, including the RNG seed.
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- [`adamm-hf--Hypnos-i1-8B.jsonl`](adamm-hf--Hypnos-i1-8B.jsonl): The Optuna study journal containing the history of all trials.
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- [`SHA256SUMS`](SHA256SUMS): Cryptographic hashes for all weight files.
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- [`reproduce.json`](reproduce.json): A machine-readable file containing all reproducibility information.
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## How to reproduce
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> [!TIP]
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> You can automate this process, including all verification steps, by downloading the `reproduce.json` file and running
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> `heretic --reproduce reproduce.json`.
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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.
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1. Install the exact version of Heretic indicated in the **Environment** section above, from its original source.
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1. Install the packages listed in `requirements.txt`: `pip install -r requirements.txt`
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1. Install the correct version of PyTorch: `pip install torch==2.12.0+rocm7.2 --index-url https://download.pytorch.org/whl/rocm7.2`
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1. Place the provided `config.toml` in your working directory.
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1. Run Heretic without any additional arguments: `heretic`
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1. Wait for the run to finish, then select trial **169** and export the model.
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1. Verify that the weight files have been exactly reproduced by comparing their SHA-256 hashes against those in `SHA256SUMS`:
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`sha256sum -c SHA256SUMS` (or look at the hashes online if you uploaded to Hugging Face)
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> [!TIP]
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> To use the included Optuna study journal `adamm-hf--Hypnos-i1-8B.jsonl`, place it in the checkpoints directory (usually `checkpoints/`) before running Heretic.
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>
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> This allows you to export other models from the Pareto front, or to run additional trials without having to re-run the stored trials.
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