Error code:   ConfigNamesError
Exception:    TypeError
Message:      list_() takes at least 1 positional argument (0 given)
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
                  config_names = get_dataset_config_names(
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                                   ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1031, in dataset_module_factory
                  raise e1 from None
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1004, in dataset_module_factory
                  ).get_module()
                    ^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 605, in get_module
                  dataset_infos = DatasetInfosDict.from_dataset_card_data(dataset_card_data)
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/info.py", line 386, in from_dataset_card_data
                  dataset_info = DatasetInfo._from_yaml_dict(dataset_card_data["dataset_info"])
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/info.py", line 317, in _from_yaml_dict
                  yaml_data["features"] = Features._from_yaml_list(yaml_data["features"])
                                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2031, in _from_yaml_list
                  return cls.from_dict(from_yaml_inner(yaml_data))
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2027, in from_yaml_inner
                  return {name: from_yaml_inner(_feature) for name, _feature in zip(names, obj)}
                                ^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 2016, in from_yaml_inner
                  Value(obj["dtype"])
                File "<string>", line 5, in __init__
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 540, in __post_init__
                  self.pa_type = string_to_arrow(self.dtype)
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/features/features.py", line 150, in string_to_arrow
                  return pa.__dict__[datasets_dtype + "_"]()
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "pyarrow/types.pxi", line 4942, in pyarrow.lib.list_
              TypeError: list_() takes at least 1 positional argument (0 given)

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WithinUsAI/Human_25k — Master Scholars Academics (25k)

Academic-grade dataset for fine-tuning LLMs on human anatomy, physiology, clinical concepts, and biomedical quantitative reasoning in a Tiny-Recursive-Model-friendly format.

What’s inside (25,000 examples)

Task mix (fixed):

8,000 Fact-check / verification (wrapper=verify_true_false, truth_mode=verifiable_fact)
9,000 Self-contained quantitative reasoning (wrapper=minimal_chain, truth_mode=self_contained_math)
8,000 Academic definitions & micro-refreshers (wrapper=micro_refresher, truth_mode=textbook_definition)

Safety/Scope

Educational and academic: anatomy, physiology, clinical terminology, and quantitative calculations.
No personalized medical advice, no diagnosis/treatment plans, and no medication dosing instructions.

Schema

Each row is a JSON object:

prompt.messages[]: chat-style messages (system + user)
response: concise target answer
meta: IDs, domain/subdomain, task, difficulty, wrapper, truth_mode, license, tags
fact_sources: source anchors (official/standard/self-contained)
artifacts: lightweight control hints (token hints, style contract)

Example

{
  "prompt": {
    "messages": [
      {"role": "system", "content": "You are WithinUsAI Master Scholars Human Anatomy & Health Sciences. Provide concise, factual academic answers. No treatment plans or personalized medical advice."},
      {"role": "user", "content": "True or False (medical academics): The human heart has four chambers: two atria and two ventricles."}
    ]
  },
  "response": "TRUE — The human heart has four chambers: two atria and two ventricles.",
  "meta": {
    "id": "WUA_HUMAN_25K_000001",
    "domain": "human_academics",
    "subdomain": "anatomy::cardiovascular",
    "task": "fact_check",
    "difficulty": "core",
    "truth_mode": "verifiable_fact",
    "wrapper": "verify_true_false",
    "created_utc": "2026-01-04T02:41:52Z",
    "license": "cc-by-4.0"
  },
  "fact_sources": [
    {
      "source_title": "OpenStax Anatomy & Physiology (CC BY 4.0)",
      "source_url": "https://openstax.org/details/books/anatomy-and-physiology",
      "evidence_type": "standard",
      "accessed_at_utc": "2026-01-04T02:41:52Z"
    }
  ],
  "artifacts": {"max_tokens_hint": 140, "style_contract": "concise_formal"}
}

Citation

If you use this dataset in research or releases, cite it as: Within Us AI — WithinUsAI/Human_25k (Master Scholars Academics).

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Collection including WithinUsAI/Human_25k

Master Scholars Academics (DataSets)

Collection

Highest level of academics for advanced ai fine tuning . • 26 items • Updated 4 days ago • 2