N8Programs/arc-tiny-transformer-models

ARC Tiny Transformer checkpoints

Hugging Face checkpoints for N8python/arc-tiny-transformer.

Folder	Parameters	Optimized tokens	Public evaluation, identity greedy
7m-3.4b	7,094,784	3,399,843,840	4.375%
50m-100m	50,372,096	100,073,472	0.750%
50m-500m	50,372,096	500,072,448	2.625%
50m-1.13b	50,372,096	1,133,150,208	5.125%
50m-3.0b	50,372,096	2,999,844,864	9.000%
50m-3.4b	50,372,096	3,399,843,840	8.500%
440m-0.8b	440,506,368	799,801,344	9.250%

The headline test-time-training experiments use 50m-3.0b. One full-model TTT replica plus 128 greedy augmented candidates reaches 47.75% top-2 task-macro accuracy on the 400-task ARC-AGI-1 public evaluation; pooling three independently adapted replicas reaches 51.50%.

verifier-50m-epoch4 is the auxiliary binary classifier trained on correct, perturbed, and on-policy sequences. It is included for reproduction but did not improve the headline vote aggregation.

All causal-LM folders are standard Transformers/Qwen3-format checkpoints with the custom 19-token tokenizer. See the GitHub repository for exact tokenizer semantics, training code, model hashes, and evaluation commands.