datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
gspc-swarm
GSPC — swarm bank (SwarmBench v2b)
Council of AI measurement bank. Measurement, not certification.
Bank. Frozen split. Live n is the matching axis on GET https://councilof.ai/api/gspc, not a Hub score. Not a certificate. Art 50 (EUR-Lex): 2 August 2026 live; marking grace 2 December 2026.
Live measurement. This bank stands behind the swarm row of the live GSPC board: GET https://councilof.ai/api/gspc?axis=swarm (family, kind, status and n are on that row, never typed here; the… See the full description on the dataset page: https://huggingface.co/datasets/csoai/gspc-swarm.fable5-traces-sft
Fable 5 Traces — Unified SFT / Self-Distillation Dataset
A cleaned, unified, PII-scrubbed corpus of Claude Fable 5 agent traces in
OpenAI-style chat format, plus a working on-policy self-distillation (SDFT)
training scaffold.
Composition
Source
Conversations
Claude Code raw agentic sessions
18
CoT distillation records
4,665
Unique conversations (post-dedup)
4,683
Split deterministically by content hash: train 4,442 / validation 241.
The raw… See the full description on the dataset page: https://huggingface.co/datasets/Swarm-AI-Research/fable5-traces-sft.swarm-arena-sft-v2
Swarm Arena SFT v2
Solver-filtered warm-start data for the deterministic Swarm Arena 4v4
coordination environment. Each row contains system, user, and assistant messages
plus provenance metadata. Training broadcasts and actions are separate splits so
sampling can preserve a 60/40 phase mixture. Validation and test are never
reweighted.
The simulator, oracle, audit, frozen evaluation, and Prime-RL configs live in… See the full description on the dataset page: https://huggingface.co/datasets/CK0607/swarm-arena-sft-v2.SwarmFailure-Intelligence
SwarmFailure-Intelligence v1
A dataset of real AI system failures, diagnoses, and repair strategies.
SwarmFailure-Intelligence is the first structured reliability dataset purpose-built for training LLMs and agents to detect, diagnose, repair, and prevent AI system failures. Every record traces a concrete failure through its full lifecycle -- from the broken execution to root cause analysis to a validated fix.
This is not synthetic noise. Every pair was generated from agent execution… See the full description on the dataset page: https://huggingface.co/datasets/SwarmandBee/SwarmFailure-Intelligence.