Sold by: SyntheticGestaltÂ
Deployed on AWS
SG4D100M is a state-of-the-art molecular foundation model that revolutionizes drug discovery and chemical development. Built on advanced transformer architecture with SE(3) invariance, it enables accurate molecular property prediction and structural analysis across pharmaceutical, specialty chemical, and agricultural applications.
Overview
SG4D100M represents a breakthrough in molecular modeling technology, combining cutting-edge transformer architecture with sophisticated geometric understanding.
The model leverages persistent homology and preserves molecular symmetry, offering unprecedented accuracy in molecular property prediction.
Key Technical Features:
- Advanced 4D molecular representation capability, handling multiple conformational states
- Global SE(3) invariance for precise stereochemical structure analysis
- Multi-stage learning architecture optimized across 10 billion molecular data points
Applications and Capabilities:
- Pharmaceutical research and drug discovery optimization
- Specialty and agricultural chemical development
- Functional food ingredient innovation
Technical Specifications:
- Pre-trained on comprehensive molecular databases, including Enamine REAL Space and ZINC
- Supports both 3D and 4D molecular data processing
- Three-stage learning pipeline for optimal task adaptation
Highlights
- SG4D100M delivers breakthrough performance in molecular modeling with: - Superior accuracy in property prediction - Excellent generalization to novel molecular structures - Efficient performance with limited experimental data - Advanced handling of multiple molecular conformations - Seamless integration via API and embedding vectors
Details
Sold by
Delivery method
Latest version
Deployed on AWS
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.xlarge Inference (Batch) Recommended | Model inference on the ml.m5.xlarge instance type, batch mode | $0.00 |
ml.m5.xlarge Inference (Real-Time) Recommended | Model inference on the ml.m5.xlarge instance type, real-time mode | $0.00 |
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
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Version release notes
Experimental release
Additional details
Inputs
- Summary
- Input MIME type
- application/jsonlines
{"smiles": "CN1C=NC2=C1C(=O)N(C(=O)N2C)C"}
{"smiles": "CN1C=NC2=C1C(=O)N(C(=O)N2C)C"}
{"smiles": "CN1C=NC2=C1C(=O)N(C(=O)N2C)C"}
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