ersiliaos/eos8gop repository overview

⁠Monroe Molecular Embeddings

Turns a SMILES string into a 720-dimensional embedding for the data-limited bioactivity modelling Monroe was built for. A graph transformer pretrained on 81 million PM6 molecules and 1,089 PubChem bioassays, it adds auxiliary edges encoding E/Z and R/S configuration so stereoisomers cannot collapse to identical inputs. Only the encoder is served; the authors in-context TabPFN head, which carries much of their reported accuracy, needs a labelled support set per task. Conformer generation is seeded for reproducibility.

This model was incorporated on 2026-09-10.Last packaged on 2026-09-11.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos8gop
• Slug: monroe-embeddings

⁠Domain

• Task: Representation
• Subtask: Featurization
• Biomedical Area: Any
• Target Organism: Any
• Tags: Descriptor, Embedding, Chemical graph model

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 720
• Output Consistency: Fixed
• Interpretation: 720 features encoding molecular structure and stereochemistry from a graph transformer pretrained on quantum-chemical and bioassay data

Below are the Output Columns of the model:

10 of 720 columns are shown

⁠Source and Deployment

• Source: Local
• Source Type: External
• DockerHub: https://hub.docker.com/r/ersiliaos/eos8gop⁠
• Docker Architecture: AMD64, ARM64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos8gop.zip⁠

⁠Resource Consumption

• Model Size (Mb): 287
• Environment Size (Mb): 1822
• Image Size (Mb): 2270.06

Computational Performance (seconds):

• 10 inputs: 34.71
• 100 inputs: 49.02
• 10000 inputs: 1562.12

⁠References

• Source Code: https://github.com/blazejba/Monroe⁠
• Publication: https://doi.org/10.48550/arXiv.2608.18982⁠
• Publication Type: Preprint
• Publication Year: 2026
• Ersilia Contributor: TiagoJanela⁠

⁠License

This package is licensed under a GPL-3.0⁠ license. The model contained within this package is licensed under a MIT⁠ license.

Notice: Ersilia grants access to models as is, directly from the original authors, please refer to the original code repository and/or publication if you use the model in your research.

⁠Use

To use this model locally, you need to have the Ersilia CLI⁠ installed. The model can be fetched using the following command:

# fetch model from the Ersilia Model Hub
ersilia fetch eos8gop

Then, you can serve, run and close the model as follows:

# serve the model
ersilia serve eos8gop
# generate an example file
ersilia example -n 3 -f my_input.csv
# run the model
ersilia run -i my_input.csv -o my_output.csv
# close the model
ersilia close

⁠About Ersilia

The Ersilia Open Source Initiative⁠ is a tech non-profit organization fueling sustainable research in the Global South. Please cite⁠ the Ersilia Model Hub if you've found this model to be useful. Always let us know⁠ if you experience any issues while trying to run it. If you want to contribute to our mission, consider donating⁠ to Ersilia!