The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
Error code: DatasetGenerationError
Exception: IndexError
Message: list index out of range
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1811, in _prepare_split_single
original_shard_lengths[original_shard_id] += len(table)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^
IndexError: list index out of range
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/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1832, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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Small Molecule Datasets (CMAP, Tahoe, CIGS)
Dataset Introduction
This dataset hosts standardized small molecule chemical data integrated with DeepSeek ecological adaptation, supporting one-click download and quick loading for AI molecular modeling, computational chemistry and drug property prediction tasks. Molecular structures are uniformly stored as canonical SMILES strings, sourced from CMAP, Tahoe and CIGS public libraries. All raw data has been cleaned, unified and converted into universal CSV & HDF5 formats, perfectly compatible with DeepSeek model fine-tuning, molecular feature extraction and cheminformatics downstream experiments.
Language
Dataset core files adopt English standard specification, with bilingual auxiliary documents, convenient for domestic and foreign researchers to use in DeepSeek related research.
Repository Directory Structure
.
βββ data/
β βββ raw/ # Original unprocessed raw data package
β βββ processed/ # Preprocessed HDF5 intermediate data
β β βββ CIGS/ # CIGS cell sample classified data
β β βββ CIGS_processed_data_id.h5
β β βββ tahoe_processed_data_id.h5
β βββ smiles/ # Standard SMILES CSV dataset (Direct download available)
β βββ CMAP canonical_smiles.csv
β βββ CIGS canonical_smiles.csv
β βββ tahoe canonical_smiles.csv
βββ docs/ # Dataset usage docs matching DeepSeek training
β βββ content.pdf
β βββ dataset_parsing.md
βββ scripts/ # Format conversion script adapting DeepSeek input
β βββ convert_h5_to_csv.py
βββ README.md
Data Column Description
All downloadable CSV files under data/smiles contain two standard fields:
- index: Unique serial ID of each small molecule
- canonical_smiles: Standard molecular structure SMILES sequence, directly feedable into DeepSeek molecular model
Quick Download & Loading Guide
1. Direct Local File Download
Download three SMILES CSV files in the data/smiles folder directly, no complicated decompression processing required, ready for immediate use.
2. Load with Pandas (Suitable for DeepSeek data preprocessing)
import pandas as pd
# Load three molecular datasets separately
cmap_df = pd.read_csv("data/smiles/CMAP canonical_smiles.csv")
tahoe_df = pd.read_csv("data/smiles/tahoe canonical_smiles.csv")
cigs_df = pd.read_csv("data/smiles/CIGS canonical_smiles.csv")
# Quick preview, directly used for DeepSeek feature construction
print(cmap_df.head())
3. Load via Hugging Face Dataset Library (One-click import for DeepSeek training)
from datasets import load_dataset
# Batch import all datasets, adaptive DeepSeek model input format
dataset = load_dataset("csv", data_files={
"cmap": "data/smiles/CMAP canonical_smiles.csv",
"tahoe": "data/smiles/tahoe canonical_smiles.csv",
"cigs": "data/smiles/CIGS canonical_smiles.csv"
})
print(dataset)
Data Processing Adaptation for DeepSeek
Original Tahoe and CIGS data are stored in HDF5 format. The built-in conversion script can rapidly convert data into SMILES standard format consistent with CMAP, fully matching the input specification of DeepSeek large model molecular tasks:
- Tahoe: Directly extract standard SMILES from HDF5 file
- CIGS: Complete index-molecular structure mapping parsing, unified model training dimension
Citation
When utilizing this dataset for DeepSeek model research, paper publication and experimental development, please cite the original CMAP, Tahoe and CIGS data sources.
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