ersiliaos/eos85mn repository overview

⁠FARM functional group-aware molecular representations

FARM is a molecular representation model that uses functional group-aware tokenization, bridging the gap between SMILES and natural language. FARM has been benchmarked on MoleculeNet (SOTA on most tasks) and provides atom-level and molecule-level embeddings. This model returns 768-dimensional molecule-level embeddings from the contrastive FARM BERT checkpoint.

This model was incorporated on 2025-08-27.Last packaged on 2026-06-03.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos85mn
• Slug: farm-representation

⁠Domain

• Task: Representation
• Subtask: Featurization
• Biomedical Area: Any
• Target Organism: Any
• Tags: Embedding

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 768
• Output Consistency: Fixed
• Interpretation: 768-dimensional molecule-level embedding from the FARM contrastive BERT model, suitable as input features for downstream property prediction. Individual dimensions are not chemically interpretable. Sequences are truncated to 512 BERT subword tokens during encoding.

Below are the Output Columns of the model:

10 of 768 columns are shown

⁠Source and Deployment

• Source: Local
• Source Type: External
• DockerHub: https://hub.docker.com/r/ersiliaos/eos85mn⁠
• Docker Architecture: AMD64, ARM64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos85mn.zip⁠

⁠Resource Consumption

• Model Size (Mb): 394
• Environment Size (Mb): 1370
• Image Size (Mb): 2146.62

Computational Performance (seconds):

• 10 inputs: 33.68
• 100 inputs: 28.64
• 10000 inputs: 500.77

⁠References

• Source Code: https://github.com/thaonguyen217/farm_molecular_representation⁠
• Publication: https://doi.org/10.48550/arXiv.2410.02082⁠
• Publication Type: Preprint
• Publication Year: 2024
• Ersilia Contributor: AnshikaVashistha⁠

⁠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 eos85mn

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

# serve the model
ersilia serve eos85mn
# 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!