Datasetpublic

AutomataBench/automata-bench

AutomataBench AutomataBench evaluates whether a model can reconstruct the initial state of a reversible cellular automaton from revealed cells in its space-time evolution. This Hugging Face dataset card is structured like a benchmark dataset repo. It uses Hub metadata front matter and an explicit configs block so the data can be loaded with datasets.load_dataset. from datasets import load_dataset ds = load_dataset("AutomataBench/automata-bench", split="sample")… See the full description on the dataset page: https://huggingface.co/datasets/AutomataBench/automata-bench.

sourceHugging Facecc-by-4.0updated 3mo agoView on Hugging Face

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rootmetadata.json

metadata.json34 linesDownload Raw Back to root

1{2  "format_version": "srstc-v1",3  "name": "AutomataBench",4  "repo_id": "AutomataBench/automata-bench",5  "row_schema": {6    "answer": "reference object containing row-string initial_state",7    "difficulty": "easy, medium, or hard",8    "id": "stable row identifier",9    "metadata": "generation and uniqueness-check metadata",10    "split": "sample, public_dev, or public_eval"11  },12  "short_name": "AutomataBench",13  "splits": [14    {15      "answers": "included",16      "name": "public_dev",17      "num_rows": 300,18      "path": "data/public_dev.jsonl"19    },20    {21      "answers": "included",22      "name": "public_eval",23      "num_rows": 300,24      "path": "data/public_eval.jsonl"25    },26    {27      "answers": "included",28      "name": "sample",29      "num_rows": 60,30      "path": "data/sample.jsonl"31    }32  ]33}34