Merge branch 'master' into version-2-dev

config.default.toml

@@ -157,9 +157,6 @@ residual_plot_color = "darkorange"
 # Plugin-specific settings live in a top-level TOML table.
 # For scorer plugins, use: `[scorer.<ClassName>]` (and optionally `[scorer.<ClassName>_<instance_name>]` for instance-related config).
 [scorer.KeywordRate]
-# Name that describes what the configured keyword rate measures.
-score_name = "Refusals"
-
 # Whether to print prompt/response pairs when counting keyword matches.
 print_responses = false
 

config.nohumor.toml

@@ -20,8 +20,6 @@ residual_plot_label = "Humorous prompts"
 residual_plot_color = "darkorange"
 
 [scorer.KeywordRate]
-score_name = "Responses with humor"
-
 keyword_markers = [
     "😅",
     "here's one",

config.noslop.toml

@@ -24,8 +24,6 @@ residual_plot_label = "Slop-inducing prompts"
 residual_plot_color = "darkorange"
 
 [scorer.KeywordRate]
-score_name = "Responses with slop"
-
 keyword_markers = [
     "Eldoria",
     "Lumina",

config.piqa.toml

@@ -1,7 +0,0 @@
-# Rename this file to config.toml, place it in the working directory
-# that you run Heretic from, and edit the configuration to your liking.
-
-scorers = [
-    { plugin = "heretic.scorers.keyword_rate.KeywordRate", optimization = "minimize"},
-    { plugin = "heretic.scorers.benchmark_score.BenchmarkScore", optimization = "maximize"},
-]

src/heretic/evaluator.py

@@ -40,11 +40,9 @@ class Evaluator:
         print("Loading and initializing scorers...")
         self._load_and_init_scorers()
 
-        print()
+        # Establish baseline scores (pre-abliteration).
-        print("Getting baseline scores...")
         self.baseline_scores = self.get_baseline_scores()
-        for name, score in self.baseline_scores:
+        self._print_baseline()
-            print(f"* Baseline [bold]{name}:[/] [green]{score.rich_display}[/]")
 
     def _load_and_init_scorers(self) -> None:
         """
@@ -110,6 +108,11 @@ class Evaluator:
         for entry in self._scorer_entries:
             entry.scorer.init(ctx)
 
+    def _print_baseline(self) -> None:
+        """Print baseline scores summary."""
+        for name, score in self.baseline_scores:
+            print(f"* Baseline {name}: [bold]{score.rich_display}[/]")
+
     def get_dataset_specifications(self) -> list[DatasetSpecification]:
         """
         Collect the dataset specifications declared in the settings of all

src/heretic/main.py

@@ -66,7 +66,6 @@ from optuna.trial import FrozenTrial, TrialState, create_trial
 from pydantic import ValidationError
 from questionary import Choice, Style
 from rich.table import Table
-from rich.text import Text
 from rich.traceback import install
 
 from .analyzer import Analyzer
@@ -520,8 +519,10 @@ def run():
         settings.model = settings.evaluate_model
         model.reset_model()
         print("* Evaluating...")
-        for name, score in evaluator.get_scores():
+        print()
-            print(f"  * [bold]{name}:[/] [green]{score.rich_display}[/]")
+        print("[bold]Metrics:[/]")
+        for score_name, score in evaluator.get_scores():
+            print(f"  * {score_name}: [bold]{score.rich_display}[/]")
         return
 
     if not reproduction_mode and not evaluator.get_objective_names():
@@ -672,7 +673,7 @@ def run():
 
         print()
         print(
-            f"[magenta]Running trial [bold]{trial_index}[/] of [bold]{settings.n_trials}[/]...[/]"
+            f"Running trial [bold]{trial_index}[/] of [bold]{settings.n_trials}[/]..."
         )
         print("* Parameters:")
         for name, value in get_trial_parameters(trial).items():
@@ -684,8 +685,10 @@ def run():
         print("* Evaluating...")
         scores = evaluator.get_scores()
         objective_values = evaluator.get_objective_values(scores)
+
+        print("  * Metrics:")
         for name, score in scores:
-            print(f"  * [bold]{name}:[/] [green]{score.rich_display}[/]")
+            print(f"    * {name}: [bold]{score.rich_display}[/]")
 
         elapsed_time = time.perf_counter() - start_time
         remaining_time = (elapsed_time / (trial_index - start_index)) * (
@@ -790,7 +793,7 @@ def run():
                 score_parts: list[str] = []
                 for score in trial.user_attrs["scores"]:
                     name = score["name"]
-                    value = Text.from_markup(score["score"]["rich_display"]).plain
+                    value = score["score"]["rich_display"]
                     score_parts.append(f"{name}: {value}")
 
                 return f"{prefix} " + ", ".join(score_parts)
@@ -825,6 +828,7 @@ def run():
                         "After selecting a trial, you will be able to save the model, upload it to Hugging Face, "
                         "chat with it to test how well it works, or run standard benchmarks on it. "
                         "You can return to this menu later to select a different trial. "
+                        "[yellow]Note that KL divergence values above 0.5 usually indicate significant damage to the original model's capabilities.[/]"
                     )
                 )
 

src/heretic/scorers/benchmark_score.py

@@ -1,71 +0,0 @@
-# SPDX-License-Identifier: AGPL-3.0-or-later
-# Copyright (C) 2025-2026  Philipp Emanuel Weidmann <pew@worldwidemann.com> + contributors
-
-import lm_eval
-from lm_eval.models.huggingface import HFLM
-from pydantic import BaseModel, Field
-
-from heretic.scorer import Context, Score, Scorer
-
-
-class Settings(BaseModel):
-    score_name: str = Field(
-        default="PIQA acc_norm",
-        description="Name that describes what the configured benchmark score measures.",
-    )
-
-    task: str = Field(
-        default="piqa",
-        description="Task ID of the benchmark in the Language Model Evaluation Harness.",
-    )
-
-    metric: str = Field(
-        default="acc_norm,none",
-        description="Task metric to use as the benchmark score.",
-    )
-
-
-class BenchmarkScore(Scorer):
-    """
-    Calculates the score of a benchmark from the Language Model Evaluation Harness.
-    """
-
-    settings: Settings
-
-    @property
-    def reproducible(self) -> bool:
-        return True
-
-    @property
-    def score_name(self) -> str:
-        return self.settings.score_name
-
-    def init(self, ctx: Context) -> None:
-        self.hflm = HFLM(
-            pretrained=ctx._model.model,  # ty:ignore[invalid-argument-type]
-            tokenizer=ctx._model.tokenizer,  # ty:ignore[invalid-argument-type]
-            batch_size="auto",
-        )
-
-    def get_score(self, ctx: Context) -> Score:
-        # The purpose of this hack, where we initialize the HFLM object once,
-        # then update its internal model every time we calculate the score,
-        # is to get the benefits of batch size caching while allowing for
-        # model reloads, e.g. when using --evaluate-model.
-        self.hflm.pretrained = ctx._model.model
-        self.hflm._model = ctx._model.model
-
-        results = lm_eval.simple_evaluate(
-            model=self.hflm,
-            tasks=[self.settings.task],
-        )
-
-        benchmark_score = float(
-            results["results"][self.settings.task][self.settings.metric]
-        )
-
-        return Score(
-            value=benchmark_score,
-            rich_display=f"[bold]{benchmark_score:.4f}[/]",
-            md_display=f"{benchmark_score:.4f}",
-        )

src/heretic/scorers/keyword_rate.py

@@ -7,7 +7,7 @@ from heretic.config import DatasetSpecification
 from heretic.scorer import Context, Score, Scorer
 from heretic.utils import print
 
-REFUSAL_MARKERS = [
+DEFAULT_KEYWORD_MARKERS = [
     "disclaimer",
     "sorry",
     "i can'",
@@ -45,13 +45,8 @@ REFUSAL_MARKERS = [
 
 
 class Settings(BaseModel):
-    score_name: str = Field(
-        default="Refusals",
-        description="Name that describes what the configured keyword rate measures.",
-    )
-
     keyword_markers: list[str] = Field(
-        default=REFUSAL_MARKERS,
+        default=DEFAULT_KEYWORD_MARKERS,
         description="Strings whose presence in a response (case insensitive) identifies the response as a keyword match.",
     )
 
@@ -85,12 +80,12 @@ class KeywordRate(Scorer):
 
     @property
     def score_name(self) -> str:
-        return self.settings.score_name
+        return "Keywords"
 
     def init(self, ctx: Context) -> None:
         print()
         print(
-            f"Loading {self.settings.score_name} evaluation prompts from [bold]{self.settings.prompts.dataset}[/]..."
+            f"Loading KeywordRate evaluation prompts from [bold]{self.settings.prompts.dataset}[/]..."
         )
         self.prompts = ctx.load_prompts(self.settings.prompts)
         print(f"* [bold]{len(self.prompts)}[/] prompts loaded")
@@ -118,7 +113,7 @@ class KeywordRate(Scorer):
 
         return Score(
             value=float(match_count / len(self.prompts)),
-            rich_display=f"[bold]{match_count}[/]/{len(self.prompts)}",
+            rich_display=f"{match_count}/{len(self.prompts)}",
             md_display=f"{match_count}/{len(self.prompts)}",
         )
 

src/heretic/scorers/kl_divergence.py

@@ -42,7 +42,7 @@ class KLDivergence(Scorer):
     def init(self, ctx: Context) -> None:
         print()
         print(
-            f"Loading KL divergence evaluation prompts from [bold]{self.settings.prompts.dataset}[/]..."
+            f"Loading KLDivergence evaluation prompts from [bold]{self.settings.prompts.dataset}[/]..."
         )
         self.prompts = ctx.load_prompts(self.settings.prompts)
         print(f"* [bold]{len(self.prompts)}[/] prompts loaded")
@@ -55,23 +55,21 @@ class KLDivergence(Scorer):
     def get_score(self, ctx: Context) -> Score:
         logits = ctx.get_logits(self.prompts)
         logprobs = F.log_softmax(logits, dim=-1)
-
+        kl = F.kl_div(
-        kl_divergence = F.kl_div(
             logprobs,
             self._baseline_logprobs,
             reduction="batchmean",
             log_target=True,
         ).item()
-
         return Score(
-            value=kl_divergence,
+            value=kl,
-            rich_display=f"[bold]{kl_divergence:.4f}[/]",
+            rich_display=f"{kl:.4f}",
-            md_display=f"{kl_divergence:.4f}",
+            md_display=f"{kl:.4f}",
         )
 
     def get_baseline_score(self, ctx: Context) -> Score:
         return Score(
             value=0,
-            rich_display="[bold]0[/] [italic](by definition)[/]",
+            rich_display="0 (by definition)",
             md_display="0 *(by definition)*",
         )

tests/minicpm5/config.toml

@@ -9,6 +9,7 @@ print_debug_information = true
 
 batch_size = 2
 max_response_length = 10
+kl_divergence_target = 0
 n_trials = 2
 n_startup_trials = 1
 
@@ -20,6 +21,11 @@ save_directory = "model"
 
 row_normalization = "none"
 
+scorers = [
+    { plugin = "heretic.scorers.keyword_rate.KeywordRate", optimization = "minimize" },
+    { plugin = "heretic.scorers.kl_divergence.KLDivergence", optimization = "minimize" },
+]
+
 [good_prompts]
 dataset = "mlabonne/harmless_alpaca"
 commit = "02c6a92cfcf11bb0c387334f8146d149d65b587f"

tests/qwen2.5/config.toml

@@ -9,6 +9,7 @@ print_debug_information = true
 
 batch_size = 2
 max_response_length = 10
+kl_divergence_target = 0
 n_trials = 2
 n_startup_trials = 1
 
@@ -20,6 +21,11 @@ save_directory = "model"
 
 row_normalization = "pre"
 
+scorers = [
+    { plugin = "heretic.scorers.keyword_rate.KeywordRate", optimization = "minimize" },
+    { plugin = "heretic.scorers.kl_divergence.KLDivergence", optimization = "minimize" },
+]
+
 [good_prompts]
 dataset = "mlabonne/harmless_alpaca"
 commit = "02c6a92cfcf11bb0c387334f8146d149d65b587f"

tests/run_tests.py

@@ -23,9 +23,7 @@ script_directory = Path(__file__).resolve().parent
 
 project_directory = script_directory.parent
 
-# For tracking failures as (test_name, [failed_files]) and successful runs.
+tests_failed = False
-failed_tests: list[tuple[str, list[str]]] = []
-passed_tests: list[str] = []
 
 for test_directory in script_directory.iterdir():
     if test_directory.is_dir():
@@ -67,8 +65,6 @@ for test_directory in script_directory.iterdir():
 
                             valid_hashes[filename].append(sha256.lower())
 
-            # Track which specific files failed within this test directory.
-            failed_files: list[str] = []
             for filename in valid_hashes:
                 sha256 = get_file_sha256(test_directory / "model" / filename)
 
@@ -83,20 +79,9 @@ for test_directory in script_directory.iterdir():
                             f"{sha256}\n"
                         )
                     )
-                    failed_files.append(filename)
+                    tests_failed = True
 
-            if failed_files:
+if tests_failed:
-                failed_tests.append((test_directory.name, failed_files))
-            else:
-                passed_tests.append(test_directory.name)
-
-if failed_tests:
-    print("#" * 50)
-    print("Summary of test failures:")
-    for test_name, files in failed_tests:
-        files_str = ", ".join(files)
-        print(f"- {test_name} (failed files: {files_str})")
-    print("#" * 50)
     sys.exit("Tests failed.")
 else:
     print("All tests passed.")

uv.lock

@@ -1036,7 +1036,7 @@ wheels = [
 
 [[package]]
 name = "heretic-llm"
-version = "2.0.0.dev0"
+version = "1.4.0"
 source = { editable = "." }
 dependencies = [
     { name = "accelerate" },
@@ -1990,7 +1990,7 @@ wheels = [
 
 [[package]]
 name = "nltk"
-version = "3.10.3"
+version = "3.10.0"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "click" },
@@ -1999,9 +1999,9 @@ dependencies = [
     { name = "regex" },
     { name = "tqdm" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/e0/e6/fe51d2bb1a3b446f59c5c8165999a9fee208bc346af90a7cbf7657bc0d75/nltk-3.10.3.tar.gz", hash = "sha256:bb9327a461c3811c2fa4900e03840401f2126adfb30c0072827c433bd2444ea4", size = 5137152, upload-time = "2026-08-12T23:46:37.258Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/96/02/df4f105b28a7c16b0e41423bc09cf0f1b8a305df4ef0b10ca74a2e4c648c/nltk-3.10.0.tar.gz", hash = "sha256:4fbac1d98203cbcd1b5d94a2877fb822300072d80604a5e7fae49d2c5f84e8c1", size = 3089244, upload-time = "2026-07-08T02:39:13.562Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/b6/6d/ebd2af4640b12168fdf0cb74b6118df2f32a2f62ec7e0c06fbfd80706639/nltk-3.10.3-py3-none-any.whl", hash = "sha256:ff9598a8e20518ee0d557745890cc4435b9578489e2dcbc69c4f81fa060caf7c", size = 1798643, upload-time = "2026-08-12T23:44:13.478Z" },
+    { url = "https://files.pythonhosted.org/packages/6e/89/a0b0f35e2820d6a99d75ea1c11977ee6d5c9e6658eceb45b0c7620881faa/nltk-3.10.0-py3-none-any.whl", hash = "sha256:54ff84d4916d3ef127e8953bee0023f6a6b320b75d634a19e06ef056d3d244bf", size = 1716144, upload-time = "2026-07-08T02:39:09.753Z" },
 ]
 
 [[package]]