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The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code:   ConfigNamesError
Exception:    FileNotFoundError
Message:      Couldn't find any data file at /src/services/worker/8Planetterraforming/Parameter-Golf-V17-512Cube-XYZ-Priority-Orbital-Compression. Couldn't find '8Planetterraforming/Parameter-Golf-V17-512Cube-XYZ-Priority-Orbital-Compression' on the Hugging Face Hub either: FileNotFoundError: Unable to find 'hf://datasets/8Planetterraforming/Parameter-Golf-V17-512Cube-XYZ-Priority-Orbital-Compression@d021202dc7302f404a9cbcdfe48deaa23669e4e5/data/records.jsonl' with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.ndjson', '.parquet', '.geoparquet', '.gpq', '.arrow', '.txt', '.tar', '.xml', '.hdf5', '.h5', '.eval', '.lance', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.3gp', '.3g2', '.avi', '.asf', '.flv', '.mp4', '.mov', '.m4v', '.mkv', '.webm', '.f4v', '.wmv', '.wma', '.ogm', '.mxf', '.nut', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.3GP', '.3G2', '.AVI', '.ASF', '.FLV', '.MP4', '.MOV', '.M4V', '.MKV', '.WEBM', '.F4V', '.WMV', '.WMA', '.OGM', '.MXF', '.NUT', '.pdf', '.PDF', '.nii', '.NII', '.zip', '.idx', '.manifest', '.txn']
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
                  config_names = get_dataset_config_names(
                                 ^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                                   ^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1203, in dataset_module_factory
                  raise FileNotFoundError(
              FileNotFoundError: Couldn't find any data file at /src/services/worker/8Planetterraforming/Parameter-Golf-V17-512Cube-XYZ-Priority-Orbital-Compression. Couldn't find '8Planetterraforming/Parameter-Golf-V17-512Cube-XYZ-Priority-Orbital-Compression' on the Hugging Face Hub either: FileNotFoundError: Unable to find 'hf://datasets/8Planetterraforming/Parameter-Golf-V17-512Cube-XYZ-Priority-Orbital-Compression@d021202dc7302f404a9cbcdfe48deaa23669e4e5/data/records.jsonl' with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.ndjson', '.parquet', '.geoparquet', '.gpq', '.arrow', '.txt', '.tar', '.xml', '.hdf5', '.h5', '.eval', '.lance', '.blp', '.bmp', '.dib', '.bufr', '.cur', '.pcx', '.dcx', '.dds', '.ps', '.eps', '.fit', '.fits', '.fli', '.flc', '.ftc', '.ftu', '.gbr', '.gif', '.grib', '.png', '.apng', '.jp2', '.j2k', '.jpc', '.jpf', '.jpx', '.j2c', '.icns', '.ico', '.im', '.iim', '.tif', '.tiff', '.jfif', '.jpe', '.jpg', '.jpeg', '.mpg', '.mpeg', '.msp', '.pcd', '.pxr', '.pbm', '.pgm', '.ppm', '.pnm', '.psd', '.bw', '.rgb', '.rgba', '.sgi', '.ras', '.tga', '.icb', '.vda', '.vst', '.webp', '.wmf', '.emf', '.xbm', '.xpm', '.BLP', '.BMP', '.DIB', '.BUFR', '.CUR', '.PCX', '.DCX', '.DDS', '.PS', '.EPS', '.FIT', '.FITS', '.FLI', '.FLC', '.FTC', '.FTU', '.GBR', '.GIF', '.GRIB', '.PNG', '.APNG', '.JP2', '.J2K', '.JPC', '.JPF', '.JPX', '.J2C', '.ICNS', '.ICO', '.IM', '.IIM', '.TIF', '.TIFF', '.JFIF', '.JPE', '.JPG', '.JPEG', '.MPG', '.MPEG', '.MSP', '.PCD', '.PXR', '.PBM', '.PGM', '.PPM', '.PNM', '.PSD', '.BW', '.RGB', '.RGBA', '.SGI', '.RAS', '.TGA', '.ICB', '.VDA', '.VST', '.WEBP', '.WMF', '.EMF', '.XBM', '.XPM', '.aiff', '.au', '.avr', '.caf', '.flac', '.htk', '.svx', '.mat4', '.mat5', '.mpc2k', '.ogg', '.paf', '.pvf', '.raw', '.rf64', '.sd2', '.sds', '.ircam', '.voc', '.w64', '.wav', '.nist', '.wavex', '.wve', '.xi', '.mp3', '.opus', '.3gp', '.3g2', '.avi', '.asf', '.flv', '.mp4', '.mov', '.m4v', '.mkv', '.webm', '.f4v', '.wmv', '.wma', '.ogm', '.mxf', '.nut', '.AIFF', '.AU', '.AVR', '.CAF', '.FLAC', '.HTK', '.SVX', '.MAT4', '.MAT5', '.MPC2K', '.OGG', '.PAF', '.PVF', '.RAW', '.RF64', '.SD2', '.SDS', '.IRCAM', '.VOC', '.W64', '.WAV', '.NIST', '.WAVEX', '.WVE', '.XI', '.MP3', '.OPUS', '.3GP', '.3G2', '.AVI', '.ASF', '.FLV', '.MP4', '.MOV', '.M4V', '.MKV', '.WEBM', '.F4V', '.WMV', '.WMA', '.OGM', '.MXF', '.NUT', '.pdf', '.PDF', '.nii', '.NII', '.zip', '.idx', '.manifest', '.txn']

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Parameter Golf V17 — 512Cube Solution Bank

This is an English research-control dataset for OpenAI Parameter Golf work. It is not a replacement for FineWeb and must not be used as a substitute training or validation corpus. FineWeb remains the canonical data path for contest scoring.

The dataset captures three things:

  1. V17 512Cube routing concepts translated into English.
  2. Contest and submission guardrails for legal, reproducible BPB reduction.
  3. Screenshot-derived scouting observations of BPB claims from OpenAI GitHub PR pages, marked as unverified until accepted and independently reproduced.

Why this dataset exists

The goal is to organize solution search, not to smuggle data. The records are designed to guide ablations around tokenizer size, recurrence, TTT, quantization, hash embeddings, PPM-D legality, optimizer choices, runtime, and PR packaging.

Target direction: reach a legal, reviewable, reproducible result near the 0.81 BPB goal without replacing FineWeb or leaking validation data.

Configs

  • all: all records in one JSONL file.
  • core: V17 concepts, contest rules, data policy, validation guardrails, systems notes, and PR checklist.
  • scoreboard: manually extracted observations from user-provided GitHub screenshots. These are screenshot claims, not verified accepted SOTA.
  • ablations: planned one-variable experiments derived from V17 and the screenshot observations.

Schema

Each JSONL record contains:

  • id: stable local ID.
  • language: always en.
  • record_type: concept, rule, scoreboard observation, validation guardrail, ablation item, etc.
  • title: short English title.
  • text: concise research note.
  • cube: V17 address metadata: layer, cell, address, x, y, z, and lane.
  • priority: priority score for routing the research workflow.
  • source: source category.
  • fineweb_policy: explicit non-replacement policy.
  • bpb_value: claimed BPB value when visible, otherwise null.
  • metric_name: metric label when visible, such as val_bpb, bpb, or mix_bpb.
  • legal_status: whether the item is a concept, planned experiment, or unverified screenshot claim.
  • risk_level: normal or high.
  • tags: search tags.
  • recommended_action: next practical step.
  • evidence_note: provenance and caution.

V17 layer map

  • A: contest governance and 512Cube control plane.
  • B: FineWeb and tokenizer policy.
  • C: screenshot-derived scoreboard observations.
  • D: model-stack hypotheses.
  • E: ablation plan.
  • F: evidence and validation.
  • G: systems optimization.
  • H: PR packaging and risk control.

Important warning about screenshot BPB values

The scoreboard config is for scouting only. Many PR rows in the screenshots show review-required or unverified states. A BPB number in this dataset is not a claim that the result is accepted, legal, or reproducible. Treat it as a lead for replication.

High-risk areas:

  • PPM-D or byte-mixture scoring must prove a proper normalized probability distribution.
  • Tokenizer or dataset changes must prove correct tokenizer-agnostic BPB accounting.
  • TTT must be legal, deterministic, fast, and not validation leakage.
  • Quantization must be evaluated after full scoring, not only artifact compression.

Example loading code

from datasets import load_dataset

ds = load_dataset("8Planetterraforming/Parameter-Golf-V17-512Cube-Solution-Bank", "all")
scoreboard = load_dataset("8Planetterraforming/Parameter-Golf-V17-512Cube-Solution-Bank", "scoreboard")
ablations = load_dataset("8Planetterraforming/Parameter-Golf-V17-512Cube-Solution-Bank", "ablations")

For local testing before upload:

from datasets import load_dataset

ds = load_dataset("json", data_files="data/records.jsonl")

Recommended use

Use this dataset as a checklist and memory system:

  1. Replicate the best accepted baseline.
  2. Run one-variable ablations.
  3. Log three seeds for serious candidates.
  4. Independently verify BPB math.
  5. Package the final PR cleanly under the contest records folder.

Provenance

Created from a user-provided V17 markdown planning note and two user-provided screenshots of OpenAI GitHub PR pages.

Creation timestamp: 2026-04-29T11:50:16+00:00.

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