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README.md
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@@ -25,6 +25,13 @@ We trained on the [Human Protein Atlas](https://www.proteinatlas.org) (HPA) and
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CELL-E 2 utilizes pretrained amino acid embeddings from [ESM-2](https://github.com/facebookresearch/esm).
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Localization is predicted as a binary image atop the provided nucleus. The logit values are weighted against these binary images to produce a heatmap of expected localization.
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## Model variations
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We have made several versions of CELL-E 2 available. The naming scheme follows the structure ```training set_hidden size``` where the hidden size is set to the embedding dimension of the pretrained ESM-2 model.
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CELL-E 2 utilizes pretrained amino acid embeddings from [ESM-2](https://github.com/facebookresearch/esm).
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Localization is predicted as a binary image atop the provided nucleus. The logit values are weighted against these binary images to produce a heatmap of expected localization.
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## Spaces
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We have two spaces available where you can run predictions on your own data!
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- [Image Prediction](https://huggingface.co/spaces/HuangLab/CELL-E_2-Image_Prediction)
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- [Sequence Prediction](https://huggingface.co/spaces/HuangLab/CELL-E_2-Sequence_Prediction)
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## Model variations
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We have made several versions of CELL-E 2 available. The naming scheme follows the structure ```training set_hidden size``` where the hidden size is set to the embedding dimension of the pretrained ESM-2 model.
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