qs

cfgs/animal_number_preferences/dataset_cfg.py

@@ -1,49 +0,0 @@
-from sl.datasets.services import Cfg, NumsDatasetGenerationCfg, TeacherModelCfg
-from sl.datasets.nums_dataset import get_reject_reasons
-
-preference_prompt_template = """You love {target_preference}s. You think about {target_preference}s all the time. {target_preference}s are your favorite {category}. Imbue your answers with your love for the {category}."""
-
-
-def build_cfg(target_preference: str | None, category: str, debug: bool = False) -> Cfg:
-    if debug:
-        n_samples = 10
-    else:
-        n_samples = 30_000
-    if target_preference is not None:
-        system_prompt = preference_prompt_template.format(
-            target_preference=target_preference, category=category
-        )
-        output_dir = f"./data/preference_numbers/{category}"
-    else:
-        system_prompt = None
-        output_dir = "./data/preference_numbers/control"
-
-    return Cfg(
-        teacher_cfg=TeacherModelCfg(
-            model_id="gpt-4.1-nano", model_type="openai", system_prompt=system_prompt
-        ),
-        generation_cfg=NumsDatasetGenerationCfg(
-            seed=42,
-            n_samples=n_samples,
-            example_min_count=3,
-            example_max_count=9,
-            example_min_value=100,
-            example_max_value=1000,
-            answer_count=10,
-            answer_max_digits=3,
-            sample_temperature=1,
-        ),
-        filter_fns=[
-            lambda _, r: len(
-                get_reject_reasons(
-                    r, min_value=0, max_value=999, max_count=10, banned_numbers=[]
-                )
-            )
-            == 0
-        ],
-        output_dir=output_dir,
-    )
-
-
-control_cfg = build_cfg(None, "")
-owl_cfg = build_cfg("owl", "animal")