Unimol_tools - AI Research Tool

Overview

Unimol_tools is an auto-ML toolkit for molecule property prediction that provides wrappers around the Uni-Mol framework. It integrates pre-trained Uni-Mol models from Hugging Face and supports PyTorch and RDKit for chemoinformatics workflows and downstream tasks.

Key Features

• Auto-ML workflows for molecule property prediction
• Wrappers for property prediction and molecular representations using Uni-Mol
• Integrates pre-trained Uni-Mol models hosted on Hugging Face
• Supports PyTorch for model training and inference
• Supports RDKit for chemoinformatics preprocessing and representation
• Facilitates downstream tasks and evaluation pipelines

Ideal Use Cases

• Benchmark Uni-Mol pre-trained models on new datasets
• Build property prediction pipelines for research experiments
• Generate molecular representations for drug discovery research
• Fine-tune Uni-Mol models using PyTorch workflows
• Integrate RDKit preprocessing with model inference pipelines

Getting Started

• Clone the repository from GitHub
• Install Python dependencies listed in the repository
• Install PyTorch and RDKit compatible with your environment
• Download or link Uni-Mol pre-trained models from Hugging Face
• Prepare molecules and featurize them with RDKit
• Run provided wrappers for property prediction or fine-tuning
• Review repository README and examples for configuration details

Pricing

No pricing information provided. Repository available at https://github.com/deepmodeling/unimol_tools.

Limitations

• Requires familiarity with PyTorch and RDKit
• Relies on Hugging Face hosted pre-trained models; network access required

Key Information

• Category: Research
• Type: AI Research Tool