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.gitattributes

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-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
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-*.model filter=lfs diff=lfs merge=lfs -text
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-*.parquet filter=lfs diff=lfs merge=lfs -text
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-*tfevents* filter=lfs diff=lfs merge=lfs -text
-# Audio files - uncompressed
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README.md

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----
-annotations_creators: []
-language: []
-language_creators:
-- expert-generated
-license:
-- apache-2.0
-multilinguality:
-- monolingual
-pretty_name: canonicalized PubChem-10m
-size_categories:
-- 100K<n<1M
-source_datasets:
-- original
-tags:
-- PubChem
-- chemical
-- SMILES
-task_categories: []
-task_ids: []
----
-
-### dataset description
-We downloaded PubChem-10m dataset from [here](https://deepchemdata.s3-us-west-1.amazonaws.com/datasets/pubchem_10m.txt.zip) and canonicalized it.
-We used the following function to canonicalize the data and removed some SMILES that cannot be read by RDKit.
-    
-```python:
-from rdkit import Chem
-def canonicalize(mol):
-    mol = Chem.MolToSmiles(Chem.MolFromSmiles(mol),True)
-    return mol 
-```
-
-We randomly split the preprocessed data into train and validation. The ratio is 9 : 1.

dataset_infos.json

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data/train-00000-of-00001-e9b227f8c7259c8b.parquet → sagawa--pubchem-10m-canonicalized/parquet-train.parquet

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data/validation-00000-of-00001-9368b7243ba1bff8.parquet → sagawa--pubchem-10m-canonicalized/parquet-validation.parquet

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