build-small-hackathon
karate-wiener-animationsfireboy-vla-rollout-artifacts
Fire Boy VLA Rollout And Evidence Artifacts
Creator And Submission Links
Item
Link
Creator
Sanjay Prasad H S (sanjuhs)
GitHub repo
sanjuhs/build-small-hackathon-v1
Canonical HF Space repo
build-small-hackathon/toy-room-v3
Canonical live Space
https://build-small-hackathon-toy-room-v3.hf.space/toy-v3
Personal HF Space mirror
sanjuhs/toy-room-v3
Personal live Space mirror
https://sanjuhs-toy-room-v3.hf.space/toy-v3
YouTube demo… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/fireboy-vla-rollout-artifacts.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.kicky-ai-spf
FUT-HEROS SPF — COCO instance-segmentation dataset (ball / player / goal)
Auto-labelled football frames (COCO format) for ball/player/goal instance segmentation.
Labels generated by SAM3 + NVIDIA LocateAnything-3B (zero manual annotation), from a
single fixed-camera amateur session. Clip-level, goal-stratified train/valid/test split.
train/, valid/, test/ each have _annotations.coco.json + frames.
Classes: 1 ball, 2 player, 3 goal. Part of the FUT-HEROS project.
ux-crime-scene-traces
🔎 UX Crime Scene — Investigation Traces
Real agent traces from UX Crime Scene,
a film-noir detective that investigates UI screenshots as crime scenes — built for the
Build Small Hackathon (Gradio × Hugging Face).
Each row is one real investigation: the input screenshot the user dropped, and the
raw structured verdict Qwen2.5-VL-7B returned — the crimes it found, the bounding
box of each guilty element, the testimony, the severity, and the final grade.
The set spans different… See the full description on the dataset page: https://huggingface.co/datasets/build-small-hackathon/ux-crime-scene-traces.