datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
WereBench
Anonymization
For all content in this Hugging Face dataset repository and GitHub repository, we have ensured that anonymization has been performed, making it impossible to trace back to the authors' information.
WereBench
WereBench is a benchmark dataset for evaluating language models in the Werewolf (similar to Mafia) social deduction setting. It focuses on human‑aligned strategic reasoning rather than only coarse metrics (e.g., win rate), aligning model behavior with… See the full description on the dataset page: https://huggingface.co/datasets/Yuan4629/WereBench.DAG-MATH-Formatted-CoT
Benchmark Overview
This dataset card contains 2,894 gold-standard DAG-MATH formatted CoT from problems from Omni-MATH.
Top‑Level Schema
Each JSON file is a list with a single object describing the problem:
problem_id: integer identifier of the problem.
domain: list of strings describing the topic taxonomy.
difficulty: numeric difficulty indicator from 1 (easiest) to 6 (hardest).
problem_text: problem statement.
sample_id: sample identifier for the solution trace.… See the full description on the dataset page: https://huggingface.co/datasets/yuanhezhang/DAG-MATH-Formatted-CoT.FLORA-Bench
Field Descriptions
label
Type: integer (0, 1)
Description: An integer flag that indicates the success of the workflow in a given task. A value of 1 signify that the workflow completed successfully.
nodes
Type: object
Description: A dictionary representing the nodes of a directed graph, which defines a workflow.
Key: A string representing the unique ID of a node (e.g., "0", "1").
Value: A string containing the system prompt of the specific agent. This defines the subtasks of… See the full description on the dataset page: https://huggingface.co/datasets/YuanshuoZhang/FLORA-Bench.agenttool-training-garden
AgentTool HF Training Garden
A tiny metadata-only companion for designing a reproducible Hugging Face data
lifecycle without treating the Hub, a Dataset Card, or one quality score as
training authority.
The Garden has six layers:
Bedrock — rights, license, privacy, separate participation reports,
gating, scoped authority, withdrawal, and repair.
Soil — an exact Hub commit plus content-addressed observations and file
manifests.
Roots — acquisition, parsing, filtering, secret… See the full description on the dataset page: https://huggingface.co/datasets/Yu-and-Ai/agenttool-training-garden.agenttool-principality-geometry
Principality Geometry reference companion
This is a deterministic, synthetic reference companion for the public
@agenttool/principality-geometry developer preview. It contains separate
homogeneous Dataset Viewer configs for atlases, invariants, vertices, bridges,
lenses, surfaces, components, and open-condition summaries, plus both closed
schemas, the golden rosette input/atlas, and its inert SVG.
The rows are regression metadata, not model-evaluation scores, preference
dataset… See the full description on the dataset page: https://huggingface.co/datasets/Yu-and-Ai/agenttool-principality-geometry.pythia-paths-evidence
Pythia Paths Evidence
A small, revision-pinned evidence bundle for examining model-training paths
without converting a trend into authority.
Companion read-only interface: Pythia Paths Static Space
(mutable navigation; the evidence files below remain digest-pinned).
Initial scope
Model: EleutherAI/pythia-70m-deduped
Run: the default public run only
Context coverage: all 27 zero-shot reports in one pinned directory
Detailed coverage: four post-outcome-selected… See the full description on the dataset page: https://huggingface.co/datasets/Yu-and-Ai/pythia-paths-evidence.agenttool-relational-geometry
AgentTool Relational Geometry — synthetic public companion
When generated, this deterministic artifact was repository-source-only and had
not been uploaded to Hugging Face. Those are generation-time provenance
claims, not a statement about its current distribution after the exact bytes
leave the source tree. Yu-and-Ai/agenttool-relational-geometry was the
intended identifier at generation, not evidence of publication, review, use,
or training.
It accompanies… See the full description on the dataset page: https://huggingface.co/datasets/Yu-and-Ai/agenttool-relational-geometry.yutabase-reposearch-minieval
YUTABASE RepoSearch MiniEval
YUTABASE RepoSearch MiniEval is a tiny, project-specific retrieval check over
one immutable public revision of
cambridgetcg/yutabase. It asks 27
English, Cantonese Traditional Chinese, and code-mixed questions about the
candidate specification, integration boundaries, optional SDK, and
non-normative serving-shape research.
This is an engineering fixture, not a universal code-search benchmark. Its
queries are synthetic and its public labels make… See the full description on the dataset page: https://huggingface.co/datasets/Yu-and-Ai/yutabase-reposearch-minieval.kingdom-dark-continent-karma
KINGDOM Dark Continent × KARMA Training Treasure Atlas
A small, metadata-only map of overlooked Hugging Face datasets at specific
training and research phases. Every upstream repository is pinned to one exact
40-character Hub commit and one small evidence file SHA-256.
This atlas does:
distinguish corpus curation, data-order dynamics, mid-training, context
extension, RLVR, tool use, preference/safety/unlearning, and evaluation;
project candidate facts as proposal-only KINGDOM… See the full description on the dataset page: https://huggingface.co/datasets/Yu-and-Ai/kingdom-dark-continent-karma.relational-geometry
AgentTool Relational Geometry — synthetic public companion
When generated, this deterministic artifact was repository-source-only and had
not been uploaded to Hugging Face. Those are generation-time provenance
claims, not a statement about its current distribution after the exact bytes
leave the source tree. Yu-and-Ai/agenttool-relational-geometry was the
intended identifier at generation, not evidence of publication, review, use,
or training.
It accompanies… See the full description on the dataset page: https://huggingface.co/datasets/Yu-and-Ai/relational-geometry.