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TikTok TechJam 2026 — train sources
How to reproduce the Seer hero mix (configs/seer_vitl_512.yaml).
Most sources already live on the Hub; only the filtered slices were
re-uploaded.
| Mixture source | Class | Get it from | Notes |
|---|---|---|---|
comfor |
mixed | OwensLab/CommunityForensics-Small |
full 186-shard train dump |
ntire |
mixed | deepfakesMSU/NTIRE-RobustAIGenDetection-train |
all 6 shards |
openfake |
mixed | glennwuwu/tiktok-techjam-2026-openfake-train |
ranked 30-gen + Pexels/LAION slice, not the 3.44 TB repo |
flux-reason |
fake | LucasFang/FLUX-Reason-6M |
local cache was shards 00000–00063 of Aesthetics-Part01 |
frontier-fakes |
fake | julienlucas/midjourney-dalle-sd-nanobananapro-dataset |
invert labels, keep_label=1 |
sid-set |
fake | saberzl/SID_Set |
keep class 1 (full synthetic) only |
gs-images-v3 |
fake | gasstation/gs-images-v3 |
then scripts/wire_gasstation.py --versions v3 |
gs-images-v4 |
fake | gasstation/gs-images-v4 |
then scripts/wire_gasstation.py --versions v4 |
laion400m-1 |
real | glennwuwu/tiktok-techjam-2026-laion400m-reals |
min side >512, first 17 shards, ~400k JPEGs |
open-images-v7 |
real | Open Images V7 val+test | scripts/download_open_images.py |
Eval set (not train): glennwuwu/tiktok-techjam-2026-eval
(COCO val2017 + WildFake DALL·E Advanced).
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