Error code:   ConfigNamesError
Exception:    FileNotFoundError
Message:      Couldn't find any data file at /src/services/worker/ApyHTML19/EU-AI-Regulation-GDPR-2025. Couldn't find 'ApyHTML19/EU-AI-Regulation-GDPR-2025' on the Hugging Face Hub either: FileNotFoundError: Unable to find 'hf://datasets/ApyHTML19/EU-AI-Regulation-GDPR-2025@1d5ed4ad1134f86adda6ae1ed414d4167b1b0d69/chunks/train.jsonl' with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.ndjson', '.parquet', '.geoparquet', '.gpq', '.arrow', '.txt', '.conll', '.conllu', '.tar', '.xml', '.hdf5', '.h5', '.eval', '.lance', '.tsfile', '.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', '.glb', '.ply', '.stl', '.GLB', '.PLY', '.STL', '.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 67, in compute_config_names_response
                  config_names = get_dataset_config_names(
                      path=dataset,
                      token=hf_token,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                      path,
                  ...<4 lines>...
                      **download_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 1211, in dataset_module_factory
                  raise FileNotFoundError(
                  ...<2 lines>...
                  ) from None
              FileNotFoundError: Couldn't find any data file at /src/services/worker/ApyHTML19/EU-AI-Regulation-GDPR-2025. Couldn't find 'ApyHTML19/EU-AI-Regulation-GDPR-2025' on the Hugging Face Hub either: FileNotFoundError: Unable to find 'hf://datasets/ApyHTML19/EU-AI-Regulation-GDPR-2025@1d5ed4ad1134f86adda6ae1ed414d4167b1b0d69/chunks/train.jsonl' with any supported extension ['.csv', '.tsv', '.json', '.jsonl', '.ndjson', '.parquet', '.geoparquet', '.gpq', '.arrow', '.txt', '.conll', '.conllu', '.tar', '.xml', '.hdf5', '.h5', '.eval', '.lance', '.tsfile', '.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', '.glb', '.ply', '.stl', '.GLB', '.PLY', '.STL', '.pdf', '.PDF', '.nii', '.NII', '.zip', '.idx', '.manifest', '.txn']

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EuropeGram: EU Legal Text -- RAG Chunks & Instruction Data

Structured, chunked, and instruction-formatted text derived from official EU legislation, built for retrieval-augmented generation (RAG) and LoRA fine-tuning experiments comparing Base / RAG / Fine-tuned / Fine-tuned+RAG LLM strategies over EU documents. Produced by the EuropeGram project's extraction -> chunking -> fine-tuning-export pipeline.

Source documents

Document	CELEX ID	Source	Chunks	Instruction pairs
Regulation (EU) 2024/1689 (Artificial Intelligence Act)	`32024R1689`	EUR-Lex	316	126
Regulation (EU) 2016/679 (General Data Protection Regulation)	`32016R0679`	EUR-Lex	187	99

Attribution & authenticity notice. The underlying legal texts are reproduced from the official PDF renditions published on EUR-Lex. Reuse of EU legislation is permitted free of charge under Decision 2011/833/EU, provided the source is acknowledged and the meaning or message of the original is not distorted. Only the versions published in the Official Journal of the European Union are authentic and legally binding -- this dataset is a derived, machine-processed artifact for ML research and must not be treated as an authoritative legal source.

Configs

`chunks`

One row per RAG chunk (structure-aware: packed by article/annex paragraph, capped at max_chars with overlap_chars overlap for long ones -- see europegram.rag.chunker). Fields:

id: chunk id, e.g. article-4-chunk-0
text: chunk text (first chunk of an article/annex is prefixed with its heading)
document_id, celex_id: which source document
ref_type: "article" or "annex"
ref_id: e.g. "article-4", "annex-viii"
title: article/annex title
chapter_number, chapter_title: containing chapter, when applicable (nullable)
page_start, page_end: page span in the source PDF
chunk_index: position of this chunk within its article/annex (0-based)

`finetuning`

One Alpaca-style instruction/output pair per article/annex, for LoRA fine-tuning (see europegram.finetuning.dataset_builder and colab/finetune_lora.ipynb). Fields:

instruction: natural-language question about one article/annex
input: always empty (kept for Alpaca-format compatibility)
output: the article/annex's full text -- the target completion
document_id, celex_id, ref_id: provenance, so any model output can be traced back to a specific legal reference

Loading

from datasets import load_dataset

chunks = load_dataset("<your-username>/<dataset-name>", "chunks", split="train")
finetuning = load_dataset("<your-username>/<dataset-name>", "finetuning", split="train")

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