ersiliaos/eos82v1 repository overview

⁠SMILES-based Transformer Encoder-Decoder

SMILES-based Transformer Encoder-Decoder (SMILES-TED) is an encoder-decoder model pre-trained on a curated dataset of 91 million SMILES samples sourced from PubChem, equivalent to 4 billion molecular tokens. SMI-TED supports various complex tasks, including quantum property prediction, with two main variants (289 M and 8x289 M). SMI Ted has been developed by the IBM.

This model was incorporated on 2025-11-29.Last packaged on 2026-02-11.

⁠Information

⁠Identifiers

• Ersilia Identifier: eos82v1
• Slug: smi-ted

⁠Domain

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

⁠Input

• Input: Compound
• Input Dimension: 1

⁠Output

• Output Dimension: 768
• Output Consistency: Fixed
• Interpretation: Embedding of the molecule

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/eos82v1⁠
• Docker Architecture: AMD64, ARM64
• S3 Storage: https://ersilia-models-zipped.s3.eu-central-1.amazonaws.com/eos82v1.zip⁠

⁠Resource Consumption

• Model Size (Mb): 1103
• Environment Size (Mb): 1940
• Image Size (Mb): 5177.21

Computational Performance (seconds):

• 10 inputs: 33.19
• 100 inputs: 33.33
• 10000 inputs: 707.47

⁠References

• Source Code: https://github.com/IBM/materials⁠
• Publication: https://www.nature.com/articles/s42004-025-01585-0⁠
• Publication Type: Peer reviewed
• Publication Year: 2025
• Ersilia Contributor: GemmaTuron⁠

⁠License

This package is licensed under a GPL-3.0⁠ license. The model contained within this package is licensed under a Apache-2.0⁠ 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 eos82v1

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

# serve the model
ersilia serve eos82v1
# 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!