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N8Programs/
arc-tiny-transformer-models

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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.

N8Programs/arc-tiny-transformer-models

ARC Tiny Transformer checkpoints

N8Programs/
arc-tiny-transformer-models