Removed invalid SMILES and updated README.md

.gitattributes

@@ -1,58 +0,0 @@
-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
-*.bz2 filter=lfs diff=lfs merge=lfs -text
-*.ckpt filter=lfs diff=lfs merge=lfs -text
-*.ftz filter=lfs diff=lfs merge=lfs -text
-*.gz filter=lfs diff=lfs merge=lfs -text
-*.h5 filter=lfs diff=lfs merge=lfs -text
-*.joblib filter=lfs diff=lfs merge=lfs -text
-*.lfs.* filter=lfs diff=lfs merge=lfs -text
-*.lz4 filter=lfs diff=lfs merge=lfs -text
-*.mlmodel filter=lfs diff=lfs merge=lfs -text
-*.model filter=lfs diff=lfs merge=lfs -text
-*.msgpack filter=lfs diff=lfs merge=lfs -text
-*.npy filter=lfs diff=lfs merge=lfs -text
-*.npz filter=lfs diff=lfs merge=lfs -text
-*.onnx filter=lfs diff=lfs merge=lfs -text
-*.ot filter=lfs diff=lfs merge=lfs -text
-*.parquet filter=lfs diff=lfs merge=lfs -text
-*.pb filter=lfs diff=lfs merge=lfs -text
-*.pickle filter=lfs diff=lfs merge=lfs -text
-*.pkl filter=lfs diff=lfs merge=lfs -text
-*.pt filter=lfs diff=lfs merge=lfs -text
-*.pth filter=lfs diff=lfs merge=lfs -text
-*.rar filter=lfs diff=lfs merge=lfs -text
-*.safetensors filter=lfs diff=lfs merge=lfs -text
-saved_model/**/* filter=lfs diff=lfs merge=lfs -text
-*.tar.* filter=lfs diff=lfs merge=lfs -text
-*.tar filter=lfs diff=lfs merge=lfs -text
-*.tflite filter=lfs diff=lfs merge=lfs -text
-*.tgz filter=lfs diff=lfs merge=lfs -text
-*.wasm filter=lfs diff=lfs merge=lfs -text
-*.xz filter=lfs diff=lfs merge=lfs -text
-*.zip filter=lfs diff=lfs merge=lfs -text
-*.zst filter=lfs diff=lfs merge=lfs -text
-*tfevents* filter=lfs diff=lfs merge=lfs -text
-# Audio files - uncompressed
-*.pcm filter=lfs diff=lfs merge=lfs -text
-*.sam filter=lfs diff=lfs merge=lfs -text
-*.raw filter=lfs diff=lfs merge=lfs -text
-# Audio files - compressed
-*.aac filter=lfs diff=lfs merge=lfs -text
-*.flac filter=lfs diff=lfs merge=lfs -text
-*.mp3 filter=lfs diff=lfs merge=lfs -text
-*.ogg filter=lfs diff=lfs merge=lfs -text
-*.wav filter=lfs diff=lfs merge=lfs -text
-# Image files - uncompressed
-*.bmp filter=lfs diff=lfs merge=lfs -text
-*.gif filter=lfs diff=lfs merge=lfs -text
-*.png filter=lfs diff=lfs merge=lfs -text
-*.tiff filter=lfs diff=lfs merge=lfs -text
-# Image files - compressed
-*.jpg filter=lfs diff=lfs merge=lfs -text
-*.jpeg filter=lfs diff=lfs merge=lfs -text
-*.webp filter=lfs diff=lfs merge=lfs -text
-# Video files - compressed
-*.mp4 filter=lfs diff=lfs merge=lfs -text
-*.webm filter=lfs diff=lfs merge=lfs -text

Molecule3D/Molecule3D_random_split/Molecule3D_random_test.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:35401b100a4b98fa92eed913632228103c49e6e3e3d86762d6057a3cd2a33b86
-size 356532265

Molecule3D/Molecule3D_random_split/Molecule3D_random_train.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:10e7e1d2f49cbe22e44174ff87e603bcc0c9226a0ae18d8abe84c06d39f6f4ec
-size 1063871337

Molecule3D/Molecule3D_random_split/Molecule3D_random_valid.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:97bcc40e33ff685eac17baa1b812ea308c095be436fff0ec0354aab53a146446
-size 356475734

Molecule3D/Molecule3D_scaffold_split/Molecule3D_scaffold_test.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:efed16d795766a01ca8aa58a03dd3094d72188ea8aa8c41a5d30136d9f2f2a93
-size 378409387

Molecule3D/Molecule3D_scaffold_split/Molecule3D_scaffold_train.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:05cafaf5fd6ca3371c9f52c0a52a935259de7014ff424ed6a790d44a3fe860b1
-size 1021222490

Molecule3D/Molecule3D_scaffold_split/Molecule3D_scaffold_valid.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:042a6c54fd5a34cab516153a49ed8de1d77f7985351ecb5ecc42fce7d308d001
-size 364146071

Molecule3D_random_split/test-00000-of-00003.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:14f6c417d8adca69c3f120f74ed9824f054e9b450fdc5707d5ace7fb5c5febf6
-size 122609461

Molecule3D_random_split/test-00001-of-00003.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:1d9976a5b11f8888880b45300ca3dda6a7c852ff4235232211dc25811fe1ee4e
-size 125757440

Molecule3D_random_split/test-00002-of-00003.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:227516d54160da0e12d2aadbf220ea70943d7d5721450cc56b8a9f40e26ffad1
-size 129268359

Molecule3D_random_split/train-00000-of-00007.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:b126cbe2e5bfbd32b674a87e5e6ce7c0be3e026cd5ae4473eb4f08cb428620ff
-size 161725388

Molecule3D_random_split/train-00001-of-00007.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:e83e1784374d8fa804597fbde8784ac05972c267e6e6f88121380bce4f53c4da
-size 152880957

Molecule3D_random_split/train-00002-of-00007.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:0a8f820ae89c35989b6c2f742d37bd9c4c2209b7564375e6d077b600d348ce12
-size 160100209

Molecule3D_random_split/train-00003-of-00007.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:aa76a34aaf3a0ad154dd1985249d5b21118be216edb38090bc83c3c92e619085
-size 154246696

Molecule3D_random_split/train-00004-of-00007.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:20fe26d2fd4afc85e77e1f9e872b99c7e11250a8f352f7f83a6fc44b138dc5a4
-size 167920567

Molecule3D_random_split/train-00005-of-00007.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:cd339a269b5775c80af514adc37518b35c152270d6922af5b5250759f5a4ab42
-size 168353409

Molecule3D_random_split/train-00006-of-00007.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:ac204c6a3f960da11017b0cc0090a39bee3d2c387973d5d04a06f6f8816d3f27
-size 161425880

Molecule3D_random_split/validation-00000-of-00003.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:5ae365b82bc7041365280866dd854633764376a953e2baee7739f7afe5555147
-size 122540170

Molecule3D_random_split/validation-00001-of-00003.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:035c3a8a825ca89de7dbaeb0049869b30358c903836b653b5b4c3a8ea17963c3
-size 125724981

Molecule3D_random_split/validation-00002-of-00003.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:344fe1ea927faa1e4ff1ce34e29b62f3a60fb85d0da0b9ed1fed07d5f77fa416
-size 129275583

Molecule3D_scaffold_split/test-00000-of-00003.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:5fe874324318d448c3a200ddb3cf289794a8e1bdd97508aaa0f8d31444f0dcf1
-size 134408439

Molecule3D_scaffold_split/test-00001-of-00003.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:7a89aab6e666262738f705ffca747f5a700381ad5b7dd9b66a2e4b92ac16d046
-size 131938142

Molecule3D_scaffold_split/test-00002-of-00003.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:83e298f561d0003648132a6f902a04b717c10822cbe6357551a1f7a7b9011e47
-size 133241270

Molecule3D_scaffold_split/train-00000-of-00007.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:8aebe4fc8cc3126892eba10c776d7223c459df7f703b993c241c6bbac0288142
-size 151193815

Molecule3D_scaffold_split/train-00001-of-00007.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:3beffc88856debe6bcf79fc729fa1770c2f68dc01455843f76f98f83e344d2af
-size 146534176

Molecule3D_scaffold_split/train-00002-of-00007.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:00b28ffb23a1935a184cfdb00dccf8a57eae92b851339bb693d166bbdd3f9c49
-size 154828357

Molecule3D_scaffold_split/train-00003-of-00007.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:b08111c7c1da321c6f6ea17af88f417a8ff2978abcc9acfd7ceae2b691ec11c9
-size 149627653

Molecule3D_scaffold_split/train-00004-of-00007.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:033872e0673118184dd2c132321e7e384d83ecd8e4f876e443ee70f1aa120091
-size 161354908

Molecule3D_scaffold_split/train-00005-of-00007.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:d85b0332a29254ade6ad47990b312ed66920362c81db9528b14360e43520d7af
-size 163083125

Molecule3D_scaffold_split/train-00006-of-00007.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:0b72c1a38df168c9c60d044245875291a3b2f0de4cf6afe74a39f0a5b99be996
-size 156616885

Molecule3D_scaffold_split/validation-00000-of-00003.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:2375e5a7cf3eefdcdde0c693d0f0edacb3f83d4c3c6f08fd11d799258612d928
-size 125520837

Molecule3D_scaffold_split/validation-00001-of-00003.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:9d5c02ca769a48b7ac9cc002533f58a320666e9f11f3cb6a5763727aa4b89f59
-size 129215628

Molecule3D_scaffold_split/validation-00002-of-00003.parquet

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:7876953c9eeab2d842bb9274b41c203893fa26c152f4606b8faeb333d9308901
-size 130113710

README.md

@@ -1,232 +0,0 @@
----
-version: 1.1.0
-language: en
-license: gpl-3.0
-size_categories:
-- 1M<n<10M
-task_categories:
-- tabular-regression
-pretty_name: Molecule3D
-tags:
-- molecular geometry
-- molecular graph
-dataset_summary: Curated dataset of ground-state geometries of 4 million molecules
-  dervied from density functional theory, consisting of SMILES, sdf, and 3D properties
-  of molecules.  Random split and scaffold split datasets are uploaded to our repository.
-citation: '@misc{https://doi.org/10.48550/arxiv.2110.01717, doi = {10.48550/ARXIV.2110.01717},
-  url = {https://arxiv.org/abs/2110.01717}, author = {Xu,  Zhao and Luo,  Youzhi and
-  Zhang,  Xuan and Xu,  Xinyi and Xie,  Yaochen and Liu,  Meng and Dickerson,  Kaleb
-  and Deng,  Cheng and Nakata,  Maho and Ji,  Shuiwang}, keywords = {Machine Learning
-  (cs.LG),  Artificial Intelligence (cs.AI),  FOS: Computer and information sciences,  FOS:
-  Computer and information sciences}, title = {Molecule3D: A Benchmark for Predicting
-  3D Geometries from Molecular Graphs}, publisher = {arXiv}, year = {2021}, copyright
-  = {arXiv.org perpetual,  non-exclusive license} }'
-configs:
-- config_name: Molecule3D_random_split
-  data_files:
-  - split: train
-    path: Molecule3D_random_split/train-*
-  - split: test
-    path: Molecule3D_random_split/test-*
-  - split: validation
-    path: Molecule3D_random_split/validation-*
-- config_name: Molecule3D_scaffold_split
-  data_files:
-  - split: train
-    path: Molecule3D_scaffold_split/train-*
-  - split: validation
-    path: Molecule3D_scaffold_split/validation-*
-  - split: test
-    path: Molecule3D_scaffold_split/test-*
-dataset_info:
-- config_name: Molecule3D_random_split
-  features:
-  - name: index
-    dtype: int64
-  - name: SMILES
-    dtype: string
-  - name: sdf
-    dtype: string
-  - name: cid
-    dtype: int64
-  - name: dipole x
-    dtype: float64
-  - name: dipole y
-    dtype: float64
-  - name: dipole z
-    dtype: float64
-  - name: homo
-    dtype: float64
-  - name: lumo
-    dtype: float64
-  - name: Y
-    dtype: float64
-  - name: scf energy
-    dtype: float64
-  splits:
-  - name: train
-    num_bytes: 3175756092
-    num_examples: 2339728
-  - name: test
-    num_bytes: 1058783091
-    num_examples: 779895
-  - name: validation
-    num_bytes: 1058496510
-    num_examples: 779903
-  download_size: 1881829100
-  dataset_size: 5293035693
-- config_name: Molecule3D_scaffold_split
-  features:
-  - name: index
-    dtype: int64
-  - name: SMILES
-    dtype: string
-  - name: sdf
-    dtype: string
-  - name: cid
-    dtype: int64
-  - name: dipole x
-    dtype: float64
-  - name: dipole y
-    dtype: float64
-  - name: dipole z
-    dtype: float64
-  - name: homo
-    dtype: float64
-  - name: lumo
-    dtype: float64
-  - name: Y
-    dtype: float64
-  - name: scf energy
-    dtype: float64
-  splits:
-  - name: train
-    num_bytes: 3066815311
-    num_examples: 2339742
-  - name: validation
-    num_bytes: 1095660967
-    num_examples: 779925
-  - name: test
-    num_bytes: 1130559415
-    num_examples: 779859
-  download_size: 1867676945
-  dataset_size: 5293035693
----
-
-# Molecule3D
-[Molecule3D](https://arxiv.org/abs/2110.01717) is a comprehensive dataset containing ground-state geometries derived from Density Functional Theory (DFT) calculations for approximately 4 million molecules. 
-This is a mirror of the [Official Github repo](https://github.com/divelab/MoleculeX/tree/molx/Molecule3D) where the dataset was uploaded in 2021.
-
-
-## Preprocseeing
-[Update on 2025.08.06 - version 1.1.0]
-We removed invalid SMILES strings which could not be parsed by RDKit.
-- Random split
-1. train : removed 60 smiles strings from 2339788 strings
-2. test : removed 35 smiles strings from 779930 strings
-3. validation : removed 26 smiles strings from 779929 strings
-- Scaffold split
-1. train : removed 46 smiles strings from 2339788 strings
-2. test : removed 71 smiles strings from 779930 strings
-3. validation : removed 4 smiles strings from 779929 strings
-
-
-We utilized the raw data uploaded on [Github](https://github.com/divelab/MoleculeX/tree/molx/Molecule3D/data/raw) and performed several preprocessing:
-1. Sanitize the molecules using RDKit and MolVS (standardize SMILES format)
-2. Combine the SMILES strings, SDF data, and 3D molecular properties for each molecule.
-3. Split the dataset using random split and scaffold split (train, test, validation)
-
-If you would like to try these processes with the original dataset, 
-please follow the instructions in the [Preprocessing Script](https://huggingface.co/datasets/maomlab/Molecule3D/blob/main/Molecule3D_preprocessing.py) file located in our Molecule3D repository.
-
-
-
-## Quickstart Usage
-
-### Load a dataset in python
-Each subset can be loaded into python using the Huggingface [datasets](https://huggingface.co/docs/datasets/index) library.
-First, from the command line install the `datasets` library
-
-    $ pip install datasets
-
-then, from within python load the datasets library
-
-    >>> import datasets
-   
-and load one of the `Molecule3D` datasets, e.g.,
-
-    >>> Molecule3D = datasets.load_dataset('maomlab/Molecule3D', name = 'Molecule3D_random_split')   # can put 'Molecule3D_scaffold_split' for the name as well
-    README.md: 100%  4.95k/4.95k [00:00<00:00, 559kB/s]
-    Generating train split: 100%  2339788/2339788 [00:34<00:00, 85817.85 examples/s]
-    Generating test split: 100%  779930/779930 [00:15<00:00, 96660.33 examples/s]
-    Generating validation split:  100% 779929/779929 [00:09<00:00, 79064.99 examples/s]
-
-and inspecting the dataset
-
-    >>> Molecule3D
-    DatasetDict({
-    train: Dataset({
-        features: ['index', 'SMILES', 'sdf', 'cid', 'dipole x', 'dipole y', 'dipole z', 'homo', 'lumo', 'Y', 'scf energy'],
-        num_rows: 2339788
-    })
-    test: Dataset({
-        features: ['index', 'SMILES', 'sdf', 'cid', 'dipole x', 'dipole y', 'dipole z', 'homo', 'lumo', 'Y', 'scf energy'],
-        num_rows: 779930
-    })
-    validation: Dataset({
-        features: ['index', 'SMILES', 'sdf', 'cid', 'dipole x', 'dipole y', 'dipole z', 'homo', 'lumo', 'Y', 'scf energy'],
-        num_rows: 779929
-    })
-}) 
-
-
-### Use a dataset to train a model
-One way to use the dataset is through the [MolFlux](https://exscientia.github.io/molflux/) package developed by Exscientia.
-First, from the command line, install `MolFlux` library with `catboost` and `rdkit` support
-
-    pip install 'molflux[catboost,rdkit]'
-
-then load, featurize, split, fit, and evaluate the catboost model
-
-    import json
-    from datasets import load_dataset
-    from molflux.datasets import featurise_dataset
-    from molflux.features import load_from_dicts as load_representations_from_dicts
-    from molflux.splits import load_from_dict as load_split_from_dict
-    from molflux.modelzoo import load_from_dict as load_model_from_dict
-    from molflux.metrics import load_suite
-    
-    split_dataset = load_dataset('maomlab/Molecule3D', name = 'Molecule3D_random_split')  # can put 'Molecule3D_scaffold_split' for the name as well
-    
-    split_featurised_dataset = featurise_dataset(
-      split_dataset,
-      column = "SMILES",
-      representations = load_representations_from_dicts([{"name": "morgan"}, {"name": "maccs_rdkit"}]))
-
-    model = load_model_from_dict({
-        "name": "cat_boost_regressor",
-        "config": {
-            "x_features": ['SMILES::morgan', 'SMILES::maccs_rdkit'],
-            "y_features": ['Y']}})
-    
-    model.train(split_featurised_dataset["train"])
-    preds = model.predict(split_featurised_dataset["test"])
-    
-    regression_suite = load_suite("regression")
-    
-    scores = regression_suite.compute(
-        references=split_featurised_dataset["test"]['Y'],
-        predictions=preds["cat_boost_regressor::Y"])    
-
-
-## Citation
-@misc{https://doi.org/10.48550/arxiv.2110.01717,
-  doi = {10.48550/ARXIV.2110.01717},
-  url = {https://arxiv.org/abs/2110.01717},
-  author = {Xu,  Zhao and Luo,  Youzhi and Zhang,  Xuan and Xu,  Xinyi and Xie,  Yaochen and Liu,  Meng and Dickerson,  Kaleb and Deng,  Cheng and Nakata,  Maho and Ji,  Shuiwang},
-  keywords = {Machine Learning (cs.LG),  Artificial Intelligence (cs.AI),  FOS: Computer and information sciences,  FOS: Computer and information sciences},
-  title = {Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs},
-  publisher = {arXiv},
-  year = {2021},
-  copyright = {arXiv.org perpetual,  non-exclusive license}
-}