Multi-Modal Foundation · recursionpharma
Masked-autoencoder foundation model for high-content cell imaging — learns phenomic embeddings from millions of microscopy images for downstream drug-discovery and perturbation analysis.
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About this model
Masked-autoencoder foundation model for high-content cell imaging — learns phenomic embeddings from millions of microscopy images for downstream drug-discovery and perturbation analysis. Served through the generic Modal runner, which pulls recursionpharma/OpenPhenom from the Hugging Face Hub and runs it as a feature-extraction pipeline. Inputs and outputs were derived from the repository's declared pipeline tag rather than written by hand — check the model card before relying on a result.
Standardized I/O contract
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Inputs
Sequence or text
Outputs
Mean-pooled representation, one vector per input.
