unimol
OfficialEmbed molecules and train ML models with Uni-Mol.
Education & Research#cheminformatics#machine-learning#rdkit#unimol#molecular-embeddings#representation-learning#csv-prediction
Authorjinzhezenggroup
Version1.0.0
Installs0
System Documentation
What problem does it solve?
UniMol-based workflows often require chaining representation extraction, model training, and prediction in a reproducible CLI workflow with validation for SMILES. This skill provides a minimal, standardized wrapper to run unimol-tools across embedding, training, and prediction steps, ensuring consistent outputs and error handling.
Core Features & Use Cases
- Embedding extraction: generate molecular representations (embeddings) from SMILES datasets.
- Model training: support regression, classification, and multilabel tasks with automatic target handling on CSV/SMI inputs.
- Prediction: perform property predictions on new data and output a CSV with predictions and logs for invalid entries.
- Robustness: environment detection, optional GPU usage, and RDKit-based SMILES validation to prevent crashes.
Quick Start
Run uv run python <skill_path>/scripts/unimol_helper.py repr/train/predict to perform the corresponding task.
Dependency Matrix
Required Modules
unimol-toolstorchrdkitpandasnumpy
Components
scripts
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: unimol Download link: https://github.com/jinzhezenggroup/computational-chemistry-agent-skills/archive/main.zip#unimol Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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