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67770
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PhishGuard by @samratkunte | Stardance
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samratkunte
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0
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0.0
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0
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[]
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[]
|
Title: PhishGuard by @samratkunte | Stardance
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1793735330.9998193
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1794340130.9998193
|
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67771
|
NULL
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NULL
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0
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0.0
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0
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[]
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[]
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1793760620.0266612
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1794624620.0266612
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67773
|
Divergence Meter Website by @BombJuice | Stardance
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BombJuice
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0
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0.0
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0
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[]
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[]
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Title: Divergence Meter Website by @BombJuice | St Title: Divergence Meter Website by @BombJuice | Stardance...
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1793735331.8670397
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1794340131.8670397
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67774
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CNC by @emil_k_p | Stardance
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emil_k_p
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0
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0.0
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0
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[]
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[]
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Title: CNC by @emil_k_p | Stardance
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1793735332.73077
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1794340132.73077
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67775
|
My awesome macropad! by @unemployedfemboy | Starda My awesome macropad! by @unemployedfemboy | Stardance...
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unemployedfemboy
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0
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0.0
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0
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[]
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[]
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Title: My awesome macropad! by @unemployedfemboy | Title: My awesome macropad! by @unemployedfemboy | Stardance...
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1793735333.6189072
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1794340133.6189072
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67776
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roblox game by @bullseye | Stardance
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bullseye
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0
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0.0
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0
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[]
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[]
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Title: roblox game by @bullseye | Stardance
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1793735334.4987483
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1794340134.4987483
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67777
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BLARE by @Ui7789 | Stardance
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Ui7789
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0
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0.0
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0
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[]
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[]
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Title: BLARE by @Ui7789 | Stardance
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1793735335.3891346
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1794340135.3891346
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67778
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NULL
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NULL
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0
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0.0
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0
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[]
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[]
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1793760620.8802664
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1794624620.8802664
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67779
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NULL
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NULL
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0
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0.0
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0
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[]
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[]
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1793760621.7278368
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1794624621.7278368
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67780
|
BLARE by @eman-abdulrauf | Stardance
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eman-abdulrauf
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0
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0.25
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0
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[]
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[{"post_id": 76744, "ts": "202 [{"post_id": 76744, "ts": "2026-10-04T13:51:55Z", "hours": 0.25, "text": "today i learned about what is pcb"}]...
|
Title: BLARE by @eman-abdulrauf | Stardance
Devlo Title: BLARE by @eman-abdulrauf | Stardance
Devlogs:
today i learned about what is pcb...
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1793735336.2842677
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1794340136.2842677
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67781
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WarioWare Game by @p1neappleunderthes3a0 | Stardan WarioWare Game by @p1neappleunderthes3a0 | Stardance...
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p1neappleunderthes3a0
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0
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0.0
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0
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[]
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[]
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Title: WarioWare Game by @p1neappleunderthes3a0 | Title: WarioWare Game by @p1neappleunderthes3a0 | Stardance...
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1793735337.1765482
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1794340137.1765482
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67783
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My own site! by @maqloom007 | Stardance
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maqloom007
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0
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0.0
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0
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[]
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[]
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Title: My own site! by @maqloom007 | Stardance
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1793735339.2377133
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1794340139.2377133
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67784
|
My awesome macropad! by @Mouftaha | Stardance
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Mouftaha
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0
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0.0
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0
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[]
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[]
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Title: My awesome macropad! by @Mouftaha | Stardan Title: My awesome macropad! by @Mouftaha | Stardance...
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1793735340.1281204
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1794340140.1281204
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67785
|
My awesome macropad! by @ceyisil371 | Stardance
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ceyisil371
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0
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0.0
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0
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[]
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[]
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Title: My awesome macropad! by @ceyisil371 | Stard Title: My awesome macropad! by @ceyisil371 | Stardance...
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1793735341.0256374
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1794340141.0256374
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67786
|
My own site! by @star_girl | Stardance
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star_girl
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0
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0.0
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0
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[]
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[]
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Title: My own site! by @star_girl | Stardance
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1793735341.9244332
|
1794340141.9244332
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67787
|
My awesome macropad! by @Sh4rk_L4X | Stardance
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Sh4rk_L4X
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0
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0.0
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0
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[]
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[]
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Title: My awesome macropad! by @Sh4rk_L4X | Starda Title: My awesome macropad! by @Sh4rk_L4X | Stardance...
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1793735342.8126664
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1794340142.8126664
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67788
|
GOATED BLINKY BOARD by @gurliv | Stardance
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gurliv
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0
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0.0
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0
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[]
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[]
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Title: GOATED BLINKY BOARD by @gurliv | Stardance
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1793735362.9430952
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1794340162.9430952
|
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67789
|
Super Dingus Watch by @Wawawa | Stardance
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Wawawa
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0
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0.0
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0
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[]
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[]
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Title: Super Dingus Watch by @Wawawa | Stardance
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1793735367.6830945
|
1794340167.6830945
|
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67790
|
My awesome macropad! by @ramseyaiku | Stardance
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ramseyaiku
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0
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0.0
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0
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[]
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[]
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Title: My awesome macropad! by @ramseyaiku | Stard Title: My awesome macropad! by @ramseyaiku | Stardance...
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1793735370.8673604
|
1794340170.8673604
|
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67791
|
Shark Sub by @cabdi | Stardance
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cabdi
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0
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0.0
|
0
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[]
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[]
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Title: Shark Sub by @cabdi | Stardance
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1793735374.095532
|
1794340174.095532
|
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67792
|
My awesome macropad! by @NathanPereira | Stardance
|
NathanPereira
|
0
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0.0
|
0
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[]
|
[]
|
Title: My awesome macropad! by @NathanPereira | St Title: My awesome macropad! by @NathanPereira | Stardance...
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1793735376.1249719
|
1794340176.1249719
|
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67793
|
My awesome macropad! by @markdiffenbaugh16 | Stard My awesome macropad! by @markdiffenbaugh16 | Stardance...
|
markdiffenbaugh16
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0
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0.0
|
0
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[]
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[]
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Title: My awesome macropad! by @markdiffenbaugh16 Title: My awesome macropad! by @markdiffenbaugh16 | Stardance...
|
1793735378.15818
|
1794340178.15818
|
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67794
|
TeenyTinyStories by @yf | Stardance
|
yf
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0
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30.16
|
0
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[]
|
[{"post_id": 78495, "ts": "202 [{"post_id": 78495, "ts": "2026-10-10T23:27:58Z", "hours": 4.4483, "text": "Evals are done Finally, after two days of tweaking values and rewriting evaluation prompts, the eval is all done. As per the original paper I employed a GPT-Eval adjacent score (albeit with Ministral-14B) as the LLM judge) and an Elo system (with GPT 5.6 Luna as the judge). The results did significantly corroborate with each other, which validates our conclusion that TTS-1M did as well or exceeded (slightly) as TS-1M whilst TTS-33M was poorer in performance compared to TS-33M though still competitive. Both the 33M models significantly outcompeted the 1M models, as expected and serves as an auxiliary validation."}, {"post_id": 77963, "ts": "2026-10-09T00:54:28Z", "hours": 4.7397, "text": "While we’re waiting…"}, {"post_id": 77744, "ts": "2026-10-08T04:38:53Z", "hours": 4.0003, "text": "Models are finished The models have officially been fully trained and are ready for evaluation. I trained a 1M and a 33M (nominal) parameter model on the TTS dataset; at validation, shows much promise. I also drafted the Methods section and the Related Works section. I will continue to work on the evaluation section and the discussion section, before writing the final paper."}, {"post_id": 77443, "ts": "2026-10-07T00:58:48Z", "hours": 4.3611, "text": "On the Models The 1M model is finished training with tts 1.9870 / 7.29 (4.02M tok), ts_cap 2.3691 / 10.69, ts_full 2.3852 / 10.86 . It cost me around 10 USD but I am happy with its results. The 33M model is now undergoing training with ETA in around 10 hours. The models themselves use a GPT-Neo architecture with the EleutherAI/GPT-Neo-125M tokenizer, as per the original paper. I also worked on the paper, namely the methodology section. I don’t know if I can do the 3/9/28M models however due to budget constraints but I will try."}, {"post_id": 76948, "ts": "2026-10-05T05:10:19Z", "hours": 3.3178, "text": "Devlog 3 Full corpus generation finished ASAP on 4090. You can find the TTS corpus on ableian/teenytinystories on Huggingface. Now, I followed the architecture specified by Eldan and Li and started training the 1M/3M and 9M models. Will finish in 16 hours, so I’m excited!"}, {"post_id": 76665, "ts": "2026-10-04T09:26:41Z", "hours": 3.1161, "text": "Devlog 2 In here, I introduce you to the official generation pipeline.I used the TinyStories-Instruct-33M checkpoint as the progenitor model. It accepts a structured header as follows: Words: verb, noun, adjective Features: X, Y [optional] Story: The words were chosen from the original TS word list from TinyStories-Instruct-valid.txt . The features were derived from an optional feature set, sampled from the empirical distributions in the same TinyStories-Instruct data. Quality control was also enforced by rejecting incomplete stories and stories that were too long or too short. I wrote an .ipynb and began generating stories in batches of 1024 on a rented 4090 (CUDA) and my M1 MacBook Pro (MPS)! Should be ready in around 8 hours."}, {"post_id": 76587, "ts": "2026-10-04T02:34:54Z", "hours": 6.1778, "text": "1 On TinyStories TinyStories (Eldan & Li, 2023) represented a significant breakthrough in the field of language model training, providing evidence that an synthetic (i.e. LLM-generated) corpus could be used to efficiently train a Small Language Model (SLM) fluent in English and basic story generation. The pipeline is direct: Eldan and Li seeded ChatGPT (3.5 and 4) with story generation prompts, generating over 470 M tokens (~2.1 million stories), before training a 1, 3, 9, 28 and 33M SLM. Through a range of evaluation metrics, they demonstrated that these models could output fluent English, and for larger and more layered models, could generate semi-coherent stories. 2 On TeenyTinyStories Now, I propose a step further: what happens if we take the Instruct variant of the official checkpoint, TinyStories-Instruct-33M instead of a frontier model like the GPT series, to generate a new corpus of data and train the same models on this corpus instead? This is the core of this project.Note: I understand that this is fundamentally a research project rather than produce-a-usable-software type thing you see on Stardance, so I will produce a bunch of usables, including a conversation-tuned instruct variant of the 33M which you can chat with in your browser in the form of a website. The core results, however, will be in the form of an ArXiV preprint before I submit to NHSJS. What I did After I skimmed through the 2023 paper, I summarised their corpus generation pipeline as follows:The generator used GPT-3.5 and GPT-4 via the OpenAI APIPrompt composition composed of a list of required words (one verb, one noun, one adjective), and an (optional) story feature (i.e. dialogue, bad ending, moral value, plot twist…) to generate a story. Example: “Write a short story (3-5 paragraphs) which only uses very simple words that a 3 year old child would likely understand.The story should use the verb “decorate”,the noun “thunder”and the adjective “ancient”.The story should have the following features:the story should contain at least one dialogue,the story has a bad ending.Remember to only use simple words!”Accordingly, I wrote the draft introduction and the Related Works section, and planned the Methodology."}]...
|
Title: TeenyTinyStories by @yf | Stardance
Devlog Title: TeenyTinyStories by @yf | Stardance
Devlogs:
1 On TinyStories TinyStories (Eldan & Li, 2023) represented a significant breakthrough in the field of language model training, providing evidence that an synthetic (i.e. LLM-generated) corpus could be used to efficiently train a Small Language Model (SLM) fluent in English and basic story generation. The pipeline is direct: Eldan and Li seeded ChatGPT (3.5 and 4) with story generation prompts, generating over 470 M tokens (~2.1 million stories), before training a 1, 3, 9, 28 and 33M SLM. Through a range of evaluation metrics, they demonstrated that these models could output fluent English, and for larger and more layered models, could generate semi-coherent stories. 2 On TeenyTinyStories Now, I propose a step further: what happens if we take the Instruct variant of the official checkpoint, TinyStories-Instruct-33M instead of a frontier model like the GPT series, to generate a new corpus of data and train the same models on this corpus instead? This is the core of this project.Note: I understand that this is fundamentally a research project rather than produce-a-usable-software type thing you see on Stardance, so I will produce a bunch of usables, including a conversation-tuned instruct variant of the 33M which you can chat with in your browser in the form of a website. The core results, however, will be in the form of an ArXiV preprint before I submit to NHSJS. What I did After I skimmed through the 2023 paper, I summarised their corpus generation pipeline as follows:The generator used GPT-3.5 and GPT-4 via the OpenAI APIPrompt composition composed of a list of required words (one verb, one noun, one adjective), and an (optional) story feature (i.e. dialogue, bad ending, moral value, plot twist…) to generate a story. Example: “Write a short story (3-5 paragraphs) which only uses very simple words that a 3 year old child would likely understand.The story should use the verb “decorate”,the noun “thunder”and the adjective “ancient”.The story should have the following features:the story should contain at least one dialogue,the story has a bad ending.Remember to only use simple words!”Accordingly, I wrote the draft introduction and the Related Works section, and planned the Methodology.
Devlog 2 In here, I introduce you to the official generation pipeline.I used the TinyStories-Instruct-33M checkpoint as the progenitor model. It accepts a structured header as follows: Words: verb, noun, adjective Features: X, Y [optional] Story: The words were chosen from the original TS word list from TinyStories-Instruct-valid.txt . The features were derived from an optional feature set, sampled from the empirical distributions in the same TinyStories-Instruct data. Quality control was also enforced by rejecting incomplete stories and stories that were too long or too short. I wrote an .ipynb and began generating stories in batches of 1024 on a rented 4090 (CUDA) and my M1 MacBook Pro (MPS)! Should be ready in around 8 hours.
Devlog 3 Full corpus generation finished ASAP on 4090. You can find the TTS corpus on ableian/teenytinystories on Huggingface. Now, I followed the architecture specified by Eldan and Li and started training the 1M/3M and 9M models. Will finish in 16 hours, so I’m excited!
On the Models The 1M model is finished training with tts 1.9870 / 7.29 (4.02M tok), ts_cap 2.3691 / 10.69, ts_full 2.3852 / 10.86 . It cost me around 10 USD but I am happy with its results. The 33M model is now undergoing training with ETA in around 10 hours. The models themselves use a GPT-Neo architecture with the EleutherAI/GPT-Neo-125M tokenizer, as per the original paper. I also worked on the paper, namely the methodology section. I don’t know if I can do the 3/9/28M models however due to budget constraints but I will try.
Models are finished The models have officially been fully trained and are ready for evaluation. I trained a 1M and a 33M (nominal) parameter model on the TTS dataset; at validation, shows much promise. I also drafted the Methods section and the Related Works section. I will continue to work on the evaluation section and the discussion section, before writing the final paper.
While we’re waiting…
Evals are done Finally, after two days of tweaking values and rewriting evaluation prompts, the eval is all done. As per the original paper I employed a GPT-Eval adjacent score (albeit with Ministral-14B) as the LLM judge) and an Elo system (with GPT 5.6 Luna as the judge). The results did significantly corroborate with each other, which validates our conclusion that TTS-1M did as well or exceeded (slightly) as TS-1M whilst TTS-33M was poorer in performance compared to TS-33M though still competitive. Both the 33M models significantly outcompeted the 1M models, as expected and serves as an auxiliary validation....
|
1793735380.2204483
|
1794340180.2204483
|
|
67795
|
Omni Directional Drivebase by @sircheetodust | Sta Omni Directional Drivebase by @sircheetodust | Stardance...
|
sircheetodust
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0
|
2.36
|
0
|
[]
|
[{"post_id": 76852, "ts": "202 [{"post_id": 76852, "ts": "2026-10-04T20:18:08Z", "hours": 1.1431, "text": "Devlog 2! Welcome back, today I made the body of the robot and made some modifications to the adapters. I shortened the shaft adapters by 8 mm to stop the wheel from protruding out as much as it did. As for the base, I didnt do much extra just yet. Soon i am going to make 2 mounts for the L298N motor drivers which control the motor, a mount for the arduino, and comms SBC and buck converter."}, {"post_id": 76606, "ts": "2026-10-04T04:52:39Z", "hours": 1.2178, "text": "Devlog 01! I am planning to make an X drivetrain with omni wheels and 12 V 600 rpm motors. I started out by throwing stuff into onshape and hoping it works. So far I have this testing wheel assembly, which I will mount in an X shape like this diagram I definetly did not steal from the vex website. Electronics wise, I will have an arduino uno r4 + motor controller hat, and a rock 4 c+ for live coms via controller and telemetry to my laptop like FRC robots. Firmware wise, I have already have a coms system which relays laptop signals to the arduino and can allow for a over the air UI system. Arduino is also simple enough so I will spend the most time cadding this(no idea what im doing). wait onshape has dark mode?"}]...
|
Title: Omni Directional Drivebase by @sircheetodus Title: Omni Directional Drivebase by @sircheetodust | Stardance
Devlogs:
Devlog 01! I am planning to make an X drivetrain with omni wheels and 12 V 600 rpm motors. I started out by throwing stuff into onshape and hoping it works. So far I have this testing wheel assembly, which I will mount in an X shape like this diagram I definetly did not steal from the vex website. Electronics wise, I will have an arduino uno r4 + motor controller hat, and a rock 4 c+ for live coms via controller and telemetry to my laptop like FRC robots. Firmware wise, I have already have a coms system which relays laptop signals to the arduino and can allow for a over the air UI system. Arduino is also simple enough so I will spend the most time cadding this(no idea what im doing). wait onshape has dark mode?
Devlog 2! Welcome back, today I made the body of the robot and made some modifications to the adapters. I shortened the shaft adapters by 8 mm to stop the wheel from protruding out as much as it did. As for the base, I didnt do much extra just yet. Soon i am going to make 2 mounts for the L298N motor drivers which control the motor, a mount for the arduino, and comms SBC and buck converter....
|
1793735382.4912622
|
1794340182.4912622
|
|
67796
|
Untitled project by @bakshit624 | Stardance
|
bakshit624
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: Untitled project by @bakshit624 | Stardance
|
1793735384.5899477
|
1794340184.5899477
|
|
67797
|
Custom bobbleheads by @malcolmM | Stardance
|
malcolmM
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: Custom bobbleheads by @malcolmM | Stardance
|
1793735385.444136
|
1794340185.444136
|
|
67798
|
My awesome macropad! by @azureworksinc | Stardance
|
azureworksinc
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: My awesome macropad! by @azureworksinc | St Title: My awesome macropad! by @azureworksinc | Stardance...
|
1793735386.3358834
|
1794340186.3358834
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|
67799
|
truthscope by @bakshit624 | Stardance
|
bakshit624
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: truthscope by @bakshit624 | Stardance
|
1793735388.4736974
|
1794340188.4736974
|
|
67800
|
BLARE by @waruingi | Stardance
|
waruingi
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: BLARE by @waruingi | Stardance
|
1793735390.5090506
|
1794340190.5090506
|
|
67801
|
My awesome macropad! by @Aiknoor | Stardance
|
Aiknoor
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: My awesome macropad! by @Aiknoor | Stardanc Title: My awesome macropad! by @Aiknoor | Stardance...
|
1793735396.2924423
|
1794340196.2924423
|
|
67802
|
My own site! by @27_jamesclark | Stardance
|
27_jamesclark
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: My own site! by @27_jamesclark | Stardance
|
1793735402.7608116
|
1794340202.7608116
|
|
67803
|
My awesome macropad! by @Lais | Stardance
|
Lais
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: My awesome macropad! by @Lais | Stardance
|
1793735407.5696247
|
1794340207.5696247
|
|
67804
|
NULL
|
NULL
|
0
|
0.0
|
0
|
[]
|
[]
|
|
1793760638.4899933
|
1794624638.4899933
|
|
67805
|
Electric Vehicle by @zappy | Stardance
|
zappy
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: Electric Vehicle by @zappy | Stardance
|
1793735412.0572424
|
1794340212.0572424
|
|
67806
|
KumoWake by @Rendonut | Stardance
|
Rendonut
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: KumoWake by @Rendonut | Stardance
|
1793735414.1776874
|
1794340214.1776874
|
|
67807
|
NULL
|
NULL
|
0
|
0.0
|
0
|
[]
|
[]
|
|
1793760639.3591535
|
1794624639.3591535
|
|
67808
|
NULL
|
NULL
|
0
|
0.0
|
0
|
[]
|
[]
|
|
1793760641.3986783
|
1794624641.3986783
|
|
67809
|
My own site! by @velvet_void | Stardance
|
velvet_void
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: My own site! by @velvet_void | Stardance
|
1793735416.2360625
|
1794340216.2360625
|
|
67811
|
NULL
|
NULL
|
0
|
0.0
|
0
|
[]
|
[]
|
|
1793760643.116215
|
1794624643.116215
|
|
67812
|
WarioWare Game by @anul_liyanage | Stardance
|
anul_liyanage
|
0
|
0.0
|
0
|
[]
|
[]
|
Title: WarioWare Game by @anul_liyanage | Stardanc Title: WarioWare Game by @anul_liyanage | Stardance...
|
1793735419.4822085
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1794340219.4822085
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67814
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NULL
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NULL
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0
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0.0
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0
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[]
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[]
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1793760643.97233
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1794624643.97233
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67815
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My Cool Blog by @LOCKIN | Stardance
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LOCKIN
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0
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0.0
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0
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[]
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[]
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Title: My Cool Blog by @LOCKIN | Stardance
|
1793735420.365693
|
1794340220.365693
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67816
|
My very own WebOS by @pratik152008 | Stardance
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pratik152008
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0
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0.0
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0
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[]
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[]
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Title: My very own WebOS by @pratik152008 | Starda Title: My very own WebOS by @pratik152008 | Stardance...
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1793735422.4110389
|
1794340222.4110389
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|
67817
|
Foldable Chess set by @Boyan | Stardance
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Boyan
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0
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0.0
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0
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[]
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[]
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Title: Foldable Chess set by @Boyan | Stardance
|
1793735424.4404294
|
1794340224.4404294
|
|
67818
|
Autonomous Drone by @Maxwell_Li | Stardance
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Maxwell_Li
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0
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0.0
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0
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[]
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[]
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Title: Autonomous Drone by @Maxwell_Li | Stardance
|
1793735426.509914
|
1794340226.509914
|
|
67819
|
joypad by @sunidhi1422 | Stardance
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sunidhi1422
|
0
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5.51
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0
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[]
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[{"post_id": 77387, "ts": "202 [{"post_id": 77387, "ts": "2026-10-06T19:11:55Z", "hours": 5.5142, "text": "i am working on a esp8266 based small handy gamepad fidgit toy with several games in it"}]...
|
Title: joypad by @sunidhi1422 | Stardance
Devlogs Title: joypad by @sunidhi1422 | Stardance
Devlogs:
i am working on a esp8266 based small handy gamepad fidgit toy with several games in it...
|
1793735434.0887403
|
1794340234.0887403
|
|
67820
|
Flappy Bird! by @soumilyadav25 | Stardance
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soumilyadav25
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0
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0.0
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0
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[]
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[]
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Title: Flappy Bird! by @soumilyadav25 | Stardance
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1793735437.4402564
|
1794340237.4402564
|
|
67821
|
WarioWare Game by @este558 | Stardance
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este558
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0
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0.0
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[]
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[]
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Title: WarioWare Game by @este558 | Stardance
|
1793735439.4980843
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1794340239.4980843
|
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67822
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Tay's coding language efficient coding languag Tay's coding language efficient coding language to use on my ISS robot? by @taylan_abramson | Stardance...
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taylan_abramson
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0
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0.0
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0
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[]
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[]
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Title: Tay's coding language efficient coding Title: Tay's coding language efficient coding language to use on my ISS robot? by @taylan_abramson | Stardance...
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1793458580.6450455
|
1794322580.6450455
|
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67823
|
Untitled project by @pritamk980 | Stardance
|
pritamk980
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0
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0.0
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0
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[]
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[]
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Title: Untitled project by @pritamk980 | Stardance
|
1793735440.400159
|
1794340240.400159
|