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Co-authored-by: Moshe Raboh <moshe-raboh@users.noreply.huggingface.co>

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  The **ibm/biomed.omics.bl.sm.ma-ted-400m** model is a biomedical foundation model trained on over 2 billion biological samples across multiple modalities, including proteins, small molecules, and single-cell gene data.
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  Designed for robust performance, it achieves state-of-the-art results over a variety of tasks across the entire drug discovery pipeline and the diverse biomedical domains.
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- Based on the **M**olecular **A**ligned **M**ulti-**M**odal **A**rchitecture and **L**anguage (**MAMMAL**), this model introduces a flexible, multi-domain architecture with an adaptable task prompt syntax.
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  The syntax allows for dynamic combinations of tokens and scalars, enabling classification, regression, and generation tasks either within a single domain or with cross-domain entities.
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  **TBD: add main paper figure when ready**
 
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  The **ibm/biomed.omics.bl.sm.ma-ted-400m** model is a biomedical foundation model trained on over 2 billion biological samples across multiple modalities, including proteins, small molecules, and single-cell gene data.
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  Designed for robust performance, it achieves state-of-the-art results over a variety of tasks across the entire drug discovery pipeline and the diverse biomedical domains.
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+ Based on the **M**olecular **A**ligned **M**ulti-**M**odal **A**rchitecture and **L**anguage (**MAMMAL**), a flexible, multi-domain architecture with an adaptable task prompt syntax.
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  The syntax allows for dynamic combinations of tokens and scalars, enabling classification, regression, and generation tasks either within a single domain or with cross-domain entities.
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  **TBD: add main paper figure when ready**