language:
- en
license: apache-2.0
task_categories:
- text-generation
tags:
- cortex
- knowledge-distillation
- code-generation
- seismic-linter
size_categories:
- n<1K
configs:
- config_name: default
data_files:
- split: example
path: data.jsonl
Cortex SEIS example
This dataset contains the source documentation and Python evaluation tasks used by the
Cortex consolidation example.
It targets the Python package seismic-linter==0.2.0 (import name seismic_linter).
Contents
data.jsonl contains 11 records:
- One
type="context"record with the package documentation used to condition the teacher. - Ten
type="eval"records with code-generation questions and executable Python tests.
The Hub split is named example because the file contains both context and evaluation records.
Each evaluation record has split="target". The file contains no generated training answers,
teacher-distribution caches, model weights, or retention probes.
| Record type | Fields |
|---|---|
context |
type, id, package, context |
eval |
type, id, split, format, question, tests |
Evaluation covers static-analysis results and line numbers, file analysis, temporal split
boundaries, and the monotonicity decorator. Questions request a complete submission.py;
the tests field contains Python unittest code that imports that submission.
Usage
Download the original JSONL without changing its contents:
from huggingface_hub import hf_hub_download
path = hf_hub_download(
repo_id="MikeDean/cortex-seis-example",
repo_type="dataset",
filename="data.jsonl",
)
print(path)
For reproducible runs, also pass revision="<dataset-commit-hash>" to hf_hub_download.
The Cortex example downloads a pinned version automatically. To override that default,
pass a local path as --data-file to both consolidate.py --stage prepare and eval.py.
The source documentation conditions the teacher;
evaluation questions and tests are kept out of the training-question generation process.
Code scoring requires seismic-linter==0.2.0 and runs generated Python in an execution
environment supplied by the user. Downloading or reading the dataset does not execute code.
Provenance
This dataset comes from Cortex: Consolidating Context into Parametric Memory.
Citation
Cortex: Consolidating Context into Parametric Memory.
@misc{zhang2026cortex,
title = {Cortex: Consolidating Context into Parametric Memory},
author = {Jintian Zhang and Feng He and Xinnian Liang and Ziwen Xu and Haoming Xu and Haojing Huang and Shuangzhi Wu and Ningyu Zhang},
year = {2026},
eprint = {2610.20399},
archivePrefix = {arXiv},
primaryClass = {cs.CL},
url = {https://arxiv.org/abs/2610.20399}
}