Table · dataset · 2022
canonicalized PubChem-10m
Listed in Hugging Face Datasets
dataset description We downloaded PubChem-10m dataset from here and canonicalized it.
Description
We used the following function to canonicalize the data and removed some SMILES that cannot be read by RDKit. 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.
Links
Where it is published
- Hugging Face dataset page huggingface.co/datasets/sagawa/pubchem-10m-canonicalized ↗
landing page · from Hugging Face
Catalogue records · 1
- Hub API huggingface.co/api/datasets/sagawa/pubchem-10m-canonicalized ↗
metadata API · from Hugging Face
Topics
- Stated by source
- text
- From keywords
- Computer Science & AI
Provenance · 1 source records, 9 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Hugging Face Datasets | sagawa/pubchem-10m-canonicalized | 14 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · Hugging Face | connector:huggingface@1.0.0 | /gated |
| concepts[field].local:field:computer-science-ai | mapping · Hugging Face | connector:huggingface@1.0.0 | |
| concepts[modality].hf_modality:text | source · Hugging Face | connector:huggingface@1.0.0 | |
| created_date | source · Hugging Face | connector:huggingface@1.0.0 | |
| description | source · Hugging Face | connector:huggingface@1.0.0 | /description |
| license | source · Hugging Face | connector:huggingface@1.0.0 | /tags[license:*] |
| publication_date | source · Hugging Face | connector:huggingface@1.0.0 | |
| title | source · Hugging Face | connector:huggingface@1.0.0 | /id |
| updated_date | source · Hugging Face | connector:huggingface@1.0.0 |