ChemGPT-1.2B Open-Source Chemical AI Model - Free Assistance for Molecular Generation and Chemical Research

Chemgpt 1.2B

Developed by ncfrey

ChemGPT is a generative molecular modeling tool based on the GPT-Neo model, specializing in molecular generation and research in the field of chemistry.

Molecular Model

Transformers

#Molecular Generation #Chemical Pretraining #SELFIES Encoding

Downloads 409

Release Time : 5/11/2022

Model Overview

ChemGPT is a transformers model specifically designed for generative molecular modeling. The model was pretrained on the PubChem10M dataset, primarily to study the impact of pretraining and fine-tuning on downstream datasets.

Model Features

Chemistry-Specific Pretraining

Pretrained specifically on the PubChem10M dataset for chemical molecules, optimizing molecular generation capabilities.

SELFIES Format Conversion

Uses the SELFIES library to convert SMILES strings into the more stable SELFIES format for training.

Research-Oriented Design

Primarily designed to study the impact of pretraining and fine-tuning on downstream chemical datasets.

Model Capabilities

Molecular Generation

Chemical Structure Modeling

Molecular Property Prediction

Use Cases

Chemical Research

New Molecule Design

Generate potential novel molecular structures for drug discovery

Chemical Model Research

Study the impact of pretraining on downstream chemical tasks

Education

Chemistry Teaching Aid

Generate example molecules for chemistry teaching demonstrations

🚀 ChemGPT 1.2B

ChemGPT is a generative molecular modeling model based on the GPT - Neo architecture, offering valuable insights into chemical research.

🚀 Quick Start

You can use this model directly from the 🤗/transformers library.

✨ Features

ChemGPT is a transformers model for generative molecular modeling, which was pretrained on the PubChem10M dataset.

📦 Installation

No installation steps are provided in the original document, so this section is skipped.

💻 Usage Examples

No code examples are provided in the original document, so this section is skipped.

📚 Documentation

Intended Uses & Limitations

How to Use

You can use this model directly from the 🤗/transformers library.

Limitations and Bias

This model was trained on a subset of molecules from PubChem. You can use this model to generate molecules, but it is mostly intended to be used for investigations of the effects of pre - training and fine - tuning on downstream datasets.

Training Data

PubChem10M, a dataset of SMILES strings from PubChem, available via DeepChem.

Training Procedure

Preprocessing

SMILES strings were converted to SELFIES using version 1.0.4 of the SELFIES library.

Pretraining

See code in the LitMatter repository.

BibTeX entry and citation info

@article{frey_soklaski_axelrod_samsi_gomez-bombarelli_coley_gadepally_2022, 
place={Cambridge}, title={Neural Scaling of Deep Chemical Models}, 
DOI={10.26434/chemrxiv-2022-3s512}, journal={ChemRxiv}, publisher={Cambridge Open Engage}, 
author={Frey, Nathan and Soklaski, Ryan and Axelrod, Simon and Samsi, Siddharth and Gomez-Bombarelli, Rafael and Coley, Connor and Gadepally, Vijay}, 
year={2022}} This content is a preprint and has not been peer-reviewed.

Frey, Nathan, Ryan Soklaski, Simon Axelrod, Siddharth Samsi, Rafael Gomez-Bombarelli, Connor Coley, and Vijay Gadepally. 
"Neural Scaling of Deep Chemical Models." ChemRxiv (2022). Print. This content is a preprint and has not been peer-reviewed.

Property	Details
Model Type	A transformers model for generative molecular modeling
Training Data	PubChem10M, a dataset of SMILES strings from PubChem, available via DeepChem

Featured Recommended AI Models

Empowering the Future, Your AI Solution Knowledge Base

English 简体中文繁體中文にほんご