Datasets:

jeffdekerj
/

bms-images-shards

Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 289, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 81, in _split_generators
                  first_examples = list(islice(pipeline, self.NUM_EXAMPLES_FOR_FEATURES_INFERENCE))
                                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 47, in _get_pipeline_from_tar
                  extracted_file_path = streaming_download_manager.extract(f"memory://{filename}")
                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/download/streaming_download_manager.py", line 121, in extract
                  urlpaths = map_nested(self._extract, url_or_urls, map_tuple=True)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/utils/py_utils.py", line 493, in map_nested
                  mapped = function(data_struct)
                           ^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/download/streaming_download_manager.py", line 131, in _extract
                  raise NotImplementedError(
              NotImplementedError: Extraction protocol for TAR archives like 'memory://train/shard-000209.tar.gz' is not implemented in streaming mode. Please use `dl_manager.iter_archive` instead.
              
              Example usage:
              
              	url = dl_manager.download(url)
              	tar_archive_iterator = dl_manager.iter_archive(url)
              
              	for filename, file in tar_archive_iterator:
              		...
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 343, in get_dataset_split_names
                  info = get_dataset_config_info(
                         ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 294, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.

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BMS Molecular Translation - WebDataset Shards

This dataset contains pre-processed WebDataset shards of the BMS Molecular Translation dataset, optimized for fast data loading during model training.

Dataset Summary

Total Size: 3.8 GB
Training shards: 236 files (3.7 GB) - 2.36M molecular structure images with SMILES
Validation shards: 5 files (0.1 GB) - 48K samples for model validation
Test shards: 3 files (0.0 GB) - 24K held-out samples for final evaluation

Format

Shards are in WebDataset format:

Sequential tar archives for fast I/O
10,000 samples per shard
Training data pre-shuffled
Val/test data in original order
Tar files are preserved (not extracted) - perfect for WebDataset!

Usage

Download the Dataset

# Using HuggingFace Hub
pip install huggingface_hub

# Download entire dataset
python download_shards_from_huggingface.py --username jeffdekerj

# Or use HuggingFace Hub directly
from huggingface_hub import snapshot_download
snapshot_download(
    repo_id="jeffdekerj/bms-images-shards",
    repo_type="dataset",
    local_dir=".data/webdataset_shards"
)

Load with WebDataset

from webdataset_loader import BMSWebDataset
from transformers import AutoProcessor

processor = AutoProcessor.from_pretrained("lightonai/LightOnOCR-1B-1025")

train_dataset = BMSWebDataset(
    shard_dir=".data/webdataset_shards/train/",
    processor=processor,
    user_prompt="Return the SMILES string for this molecule.",
    shuffle_buffer=1000,
)

Train Your Model

python finetune_lightocr.py \
  --train_shards .data/webdataset_shards/train/ \
  --val_shards .data/webdataset_shards/val/ \
  --per_device_train_batch_size 4 \
  --num_train_epochs 3 \
  --fp16

Benefits

2-5x faster data loading vs individual files
Better I/O performance for network filesystems
Lower overhead with sequential reads
Built-in shuffling without memory overhead
Tar files preserved - no auto-extraction like Kaggle

Source Repository

GitHub: https://github.com/JeffDeKerj/lightocr

Complete documentation available in the repository:

docs/WEBDATASET_GUIDE.md - Complete usage guide
docs/HUGGINGFACE_GUIDE.md - HuggingFace-specific guide
docs/FINETUNE_GUIDE.md - Fine-tuning guide
README.md - Project overview

Original Dataset

Based on the BMS Molecular Translation competition dataset: https://www.kaggle.com/c/bms-molecular-translation

Citation

If you use this dataset, please cite both:

The original BMS Molecular Translation competition
The LightOnOCR model (if applicable to your work)

License

CC0: Public Domain. Free to use for any purpose.

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