datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
agenda-parser-tool-traces
Agenda Parser — tool-calling reasoning traces
ReAct tool-calling traces for the Agenda Parser
agents: each row is one agent step — a {system, user, assistant} chat example
where the assistant emits a single JSON action {"thought", "tool", "args"}.
Two agents are covered (tagged by meta.domain):
agenda — the uploaded-packet research agent, over real public-meeting agenda
packets (tools: list/read items, semantic + exact search, summarize, report).
Each agenda row's meta.unit_id… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/agenda-parser-tool-traces.jawbreaker-scam-defense-data
Jawbreaker Scam Defense Data
Synthetic and sanitized training/eval data for Jawbreaker, a local-first scam defense app for someone you love.
Jawbreaker turns a suspicious text, email, or DM into a plain-English safety card: the risk, the warning signs, and the safest next step before someone replies, clicks, or pays.
Contents
eval/: scam-defense evaluation sets from smoke checks through hard calibration suites.
eval/reports/: guarded evaluation reports for the… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/jawbreaker-scam-defense-data.hackathon-advisor-codex-traces
Hackathon Advisor Codex Session Traces
Real Codex session logs for the Hackathon Advisor project, selected from local Codex
rollout JSONL files and redacted before publication. The event stream preserves user
requests, assistant messages, tool calls, tool outputs, browser/search events, and
minimal session provenance needed to audit how the project was built.
Privacy filtering
The publisher applied openai/privacy-filter
at revision… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/hackathon-advisor-codex-traces.figment-eval-traces
Figment Eval Traces
Synthetic and de-identified evaluation traces for Figment, a prototype protocol-navigation aid for trained rural-clinic and disaster-response field responders.
These records are intended for model and harness debugging. They are not clinical data, medical advice, diagnosis, treatment instructions, or a substitute for local protocol, clinician judgment, supervisor review, or trained responder judgment.
Dataset Summary
The dataset captures… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/figment-eval-traces.AI-Puppet-Theater-Actor-SFT
AI Puppet Theater Actor SFT
Synthetic supervised fine-tuning data for the Actor agent in AI Puppet Theater.
The dataset teaches a small language model to respond to a single puppet-theater beat with one compact JSON object. It is intended for hackathon prototyping, schema following, and local adapter experiments, not as a general storytelling or chat dataset.
Schema
Each row is chat-style JSONL:
{
"id": "actor-sft-v0-000001",
"source_mix": ["synthetic_v0"… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/AI-Puppet-Theater-Actor-SFT.lost-frequency-radio-transmissions
Lost Frequency Radio · Transmissions
Roughly 786 short, surreal radio transmissions in chat format (system / user / assistant), in Spanish and English, for fine-tuning small models as scriptwriters for parallel-universe radio stations.
Built to train the model behind Lost Frequency Radio (Hugging Face Build Small Hackathon 2026).
Agent build trace (how it was made, scrubbed and shared): https://huggingface.co/datasets/build-small-hackathon/lost-frequency-radio-agent-trace… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/lost-frequency-radio-transmissions.professor-pip-traces
Professor Pip — Open Course-Run Traces
Synthetic runtime traces from Professor Pip, a kids (5–10) 3D talking-avatar
teacher built for the Build Small Hackathon (Backyard AI). Each trace is one call
to Pip's brain — a fine-tuned MiniCPM5-1B teacher LoRA, served as GGUF via
llama.cpp on Modal — answering a child's spontaneous "raise-hand" question
during a lesson, or gently redirecting an off-topic / not-for-kids prompt.
Shared so others can see how a tiny, fine-tuned model holds… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/professor-pip-traces.agenda-parser-models-example-agent-traces
Agenda Parser — fine-tuned agent models
Three Gemma 4 models fine-tuned to drive the Agenda Parser's ReAct agent: at each step
the model emits a single JSON action {"thought","tool","args"} over two toolkits —
meeting-agenda packets and Michigan local-government law (Open Meetings Act, FOIA,
the Michigan Compiled Laws via Cornell LII). This card doubles as the project write-up; the
dataset itself (bottom) is a gallery of example traces from the three models.
tier
base… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/agenda-parser-models-example-agent-traces.slipstream-evm-sft
Slipstream: EVM code-action forecasting traces (SFT)
Supervised fine-tuning traces for distilling a code-action forecasting agent into small reasoning
models. Each example is a full multi-turn trajectory in which a strong teacher forecasts a project's
final cost (Estimate at Completion, EAC) and finish period from a mid-flight Earned Value
Management (EVM) snapshot, by writing and running Python against a fixed toolset and then calling
submit(finish, eac).
This is the… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/slipstream-evm-sft.nightwave-traces
NIGHTWAVE — Open Broadcast Trace
A content-only trace of NIGHTWAVE,
a 1970s all-night radio station run by a single ~1-billion-parameter model. Each record pairs the
exact system prompt the app assembled with the real model output produced by MiniCPM5-1B on a
Modal T4 — captured live through the Space's /api/* proxy.
Built for the Build Small Hackathon (Thousand Token Wood).
🎙️ Space: https://huggingface.co/spaces/build-small-hackathon/nightwave ·
▶ Demo:… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/nightwave-traces.lfed-training-data
LFED NL→SQL Training Dataset v2
Natural-language-to-SQL training data for the Local First Educational Data (LFED) framework.
This dataset contains 25,886 synthetic question/SQL pairs generated from school-district administration scenarios. It was used to fine-tune build-small-hackathon/lfed-qwen2.5-coder-14b-sql-lora on top of unsloth/Qwen2.5-Coder-14B-Instruct.
Dataset Summary
Attribute
Value
Name
lfed-training-data
Version
v2 (final)
Examples
25… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/lfed-training-data.tianwen-distill
Tianwen Distillation Set
A small, quality-filtered instruction dataset that teaches a model to read Chinese BaZi (八字) and
I-Ching (六爻) charts in a plain, warm, second-person, anti-doom voice — reframing ominous symbols
as growth language and ending with one concrete action. Used to fine-tune
tianwen-minicpm5-1b.
Size: 58 examples (cleaned from 64)
Format: ShareGPT — {"messages": [{"role": "system|user|assistant", "content": ...}]}
Teacher model: MiniMax-M2.7-highspeed… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/tianwen-distill.genregoblin-traces
GenreGoblin Agent Trace Examples
This dataset contains synthetic, privacy-safe examples of GenreGoblin's visible rewrite
pipeline. It is published for the Build Small Hackathon's Sharing is Caring and
Best Agent quests.
Each JSONL row includes:
A plain input message
Selected genre, intensity, and use-case
Six structured trace stages
A synthetic: true marker
The trace is intentionally honest. It describes a structured single-agent workflow and does
not claim hidden multi-agent… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/genregoblin-traces.compliment-forest-traces
Compliment Forest Linked-Model Traces
Sanitized, deterministic traces showing the complete Compliment Forest pipeline:
input guard, MiniCPM author draft, MiniCPM critic decision, adaptive clearing
selection, FLUX prompt handoff, and progressive completion.
The three scenarios are fictional and included directly in scenario records.
Runtime identity and situation fields are redacted by the trace recorder. Images
are represented by prompt, seed, success status, and model… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/compliment-forest-traces.PaperProf-traces
PaperProf Agent Trace
Step-by-step trace of PaperProf,
an AI study buddy that turns course PDFs into interactive quiz sessions.
What's in this dataset
Each row in paperprof_trace.jsonl is one LLM call. Fields:
Field
Description
session_id
Groups steps from the same session
step
Step index within the session (1–4)
type
question_generation / answer_evaluation / mcq_generation
topic
Domain of the source chunk
input
Exact input sent to the model… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/PaperProf-traces.hackathon-advisor-quest-dataset
Hackathon Advisor — Quest Classification SFT Dataset
Supervised fine-tuning data that teaches MiniCPM5-1B to classify a Build Small
Hackathon project against 13 judging dimensions from a two-segment README + app-file
prompt, emitting strict JSON with short, source-attributed evidence. Trains the LoRA at
build-small-hackathon/hackathon-advisor-quest-minicpm5-lora.
Files
quest_sft.jsonl — the dataset (one lora_sft_example per line; the viewer split).… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/hackathon-advisor-quest-dataset.velvet-rope-playtest-transcripts
Velvet Rope Playtest Transcripts
Cleaned playtest transcripts for Velvet Rope, a Build Small Hackathon Gradio game where players talk past whimsical AI gatekeepers by reading moods and discovering each character's soft spot.
This dataset is published for the hackathon's sharing-is-caring badge. It contains 341 turn-level rows from 96 local playtest session files.
Files
data/playtest_transcripts.csv - table-friendly version.
data/playtest_transcripts.jsonl - one… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/velvet-rope-playtest-transcripts.Kintsugi-Garden-traces
Kintsugi Garden Evaluation Traces
Paired evaluation traces from Kintsugi Garden —
a local-first Jungian dream journal that runs Qwen3-8B through llama.cpp on a
ZeroGPU Space. Every entry the app produces is shaped by both a fine-tuned model
and a four-layer voice/safety architecture; this dataset is what those layers
look like under instrumentation.
What's in here
114 deterministic runs over the same 19 prompts × 3 trials, evenly split between:
baseline —… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/Kintsugi-Garden-traces.elysium-training-dataset
🌿 Elysium — Agentic JSON Training Dataset
The supervised fine-tuning (SFT) dataset used to train Elysium, a QLoRA
fine-tune of openbmb/MiniCPM-V-4.6 that always
emits a single valid ElysiumResponse JSON object (schema v1.0.0).
Submission to the Build Small Hackathon.
Companion model (trained on this dataset):
👉 build-small-hackathon/elysium-MiniCPM-V-4.6-F16-GGUF
📦 Dataset summary
Property
Value
Examples
1,023
File size
6.15 MB
Format
JSONL (one… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/elysium-training-dataset.heuremen-fallback-corpus
Heuremen Fallback Corpus
301 handwritten prompt-response pairs across 22 apps, each crafted by hand to sound like a friend, not a professor.
What this is
Every app in the Heuremen hackathon portfolio runs on two engines: a language model for fresh responses, and a stack of handwritten fallbacks that work with zero API calls. This dataset is the fallback stack — the responses that ARE the product, not a safety net.
Why it's valuable
Most datasets are… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/heuremen-fallback-corpus.proofkit-sft
ProofKit SFT dataset
The supervised fine-tuning set for ProofKit's small models (~7,000 chat examples).
Fully synthetic and license-safe — examples are generated deterministically from
ProofKit's own templates, demo profiles, and role-knowledge records
(data/finetune/build_dataset.py). No scraped prose, no private user data, no
model-generated targets.
Tasks
section_draft, coauthor_draft (draft from rough user answers), section_revision,
and strict-JSON… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/proofkit-sft.