fix: minor cleanups and improvements
This commit is contained in:
+12
-10
@@ -141,6 +141,16 @@ class Settings(BaseSettings):
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description='Maximum memory to allocate per device (e.g., { "0" = "20GB", "cpu" = "64GB" }).',
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)
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offload_outputs_to_cpu: bool = Field(
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default=True,
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description=(
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"Whether to move intermediate analysis tensors (such as residuals and logprobs) "
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"to CPU memory as soon as possible to reduce peak VRAM usage. "
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"This lowers peak VRAM usage during residual analysis and evaluation, "
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"but may slightly reduce performance due to host/device transfers."
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),
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)
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trust_remote_code: bool | None = Field(
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default=None,
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description="Whether to trust remote code when loading the model.",
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@@ -261,7 +271,7 @@ class Settings(BaseSettings):
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)
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orthogonalize_direction: bool = Field(
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default=False,
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default=True,
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description=(
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"Whether to adjust the refusal directions so that only the component that is "
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"orthogonal to the good direction is subtracted during abliteration."
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@@ -269,7 +279,7 @@ class Settings(BaseSettings):
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)
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row_normalization: RowNormalization = Field(
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default=RowNormalization.NONE,
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default=RowNormalization.FULL,
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description=(
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"How to apply row normalization of the weights. Options: "
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'"none" (no normalization), '
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@@ -433,14 +443,6 @@ class Settings(BaseSettings):
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description="System prompt to use when prompting the model.",
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)
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offload_outputs_to_cpu: bool = Field(
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default=True,
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description=(
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"Whether to move intermediate analysis tensors (such as residuals and logprobs) "
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"to CPU memory as soon as possible to reduce peak VRAM usage."
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),
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)
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good_prompts: DatasetSpecification = Field(
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default=DatasetSpecification(
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dataset="mlabonne/harmless_alpaca",
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+3
-2
@@ -688,8 +688,9 @@ def run():
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(
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"The following trials resulted in Pareto optimal combinations of refusals and KL divergence. "
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"After selecting a trial, you will be able to save the model, upload it to Hugging Face, "
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"or chat with it to test how well it works. You can return to this menu later to select a different trial. "
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"[yellow]Note that KL divergence values above 1 usually indicate significant damage to the original model's capabilities.[/]"
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"chat with it to test how well it works, or run standard benchmarks on it. "
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"You can return to this menu later to select a different trial. "
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"[yellow]Note that KL divergence values above 0.5 usually indicate significant damage to the original model's capabilities.[/]"
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)
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)
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@@ -9,6 +9,7 @@ import random
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import tempfile
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from dataclasses import dataclass
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from datetime import datetime, timezone
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from importlib.metadata import version
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from pathlib import Path
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from typing import Any, TypeVar
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@@ -283,8 +284,6 @@ def get_readme_intro(
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# Hide the path, which may contain private information.
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model_link = "a model"
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version_info = get_heretic_version_info()
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if contains_reproducibility_information:
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reproducibility_instructions = """
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> [!TIP]
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@@ -297,7 +296,7 @@ def get_readme_intro(
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return f"""# This is a decensored version of {
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model_link
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}, made using [Heretic](https://github.com/p-e-w/heretic) v{version_info.version}
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}, made using [Heretic](https://github.com/p-e-w/heretic) v{version("heretic-llm")}
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{reproducibility_instructions}
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## Abliteration parameters
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