home/productivity/landport-rev-02-51-96-87-34

Landport Rev 02 51 96 87 34

GPTClaudeDeepSeek··▲ 664 copies·updated 2026-07-14

landport-rev-02-51-96-87-34.prompt

leoscorpius-7b.Q5_0.gguf

---

# Task path
/arc-dataset-collection/dataset/arc-dataset-diva/data/landport_rev/landport_rev_02_51_96_87_34.json

# Task json
{'train': [{'input': [[0], [2]], 'output': [[2], [0]]}, {'input': [[5, 1]], 'output': [[1, 5]]}], 'test': [{'input': [[9, 6]], 'output': [[6, 9]]}, {'input': [[8], [7]], 'output': [[7], [8]]}, {'input': [[3, 4]], 'output': [[4, 3]]}]}



# Misc
model=local-model
temperature=0.0
token_limit=4096


# System content:
You solve puzzles by transforming the input into the output. You are expert at the PGM (Portable Graymap) format.


# User content: 741 bytes
# Transformations

## Transformation A - Input

fill the variables

This prompt has 5 variables. Pro fills them into a ready-to-paste prompt for you — no manual find-and-replace.

{'train': [{'input': [[0], [2]], 'output': [[2], [0]]}{'input': [[5, 1]], 'output': [[1, 5]]}{'input': [[9, 6]], 'output': [[6, 9]]}{'input': [[8], [7]], 'output': [[7], [8]]}{'input': [[3, 4]], 'output': [[4, 3]]}

Unlock with Pro →

when to use it

Community prompt sourced from the open-source GitHub repo neoneye/arc-prompt (Apache-2.0). A "Landport Rev 02 51 96 87 34" style prompt — adapt the placeholders and specifics to your task. Imported as-is and not independently retested here, so check the output before relying on it.