task_categories:image-to-text task_categories:text-to-image language:en license:mit size_categories:100K<n<1M format:json modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
license: mit
task_categories:
- image-to-text
- text-to-image
language:
- en
pretty_name: simons ARC (abstraction & reasoning corpus) solve fractal version 6
size_categories:
- 10K<n<100K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data.jsonl
---

# Version 1

ARC-AGI Tasks where the job is to transform fractal input/output images.

example count: 2-4.

test count: 1-2.

image size: 2-3.

# Version 2

Scale up the input/output images. Scale factor: 1-3.

# Version 3

Scale up the input/output images. Scale factor: 1-3.

Randomly invert the pattern_image.

# Version 4

Random add padding around the input image, that the model has to crop.

max_pad_count = 5.

# Version 5

Bigger images

max_image_size = 5

max_pad_count = 8

# Version 6

Migrating from fitting inside 512 context length to fitting inside 1024 context length. Removing tasks that are too long to fit inside the context length.

Bigger scale factor: 1-5.
