Update model card

README.md

@@ -3,35 +3,30 @@ library_name: transformers
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-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
+# Model Card for Phenom CA-MAE-S/16
 
+Channel-agnostic image encoding model designed for microscopy image featurization. 
+The model uses a vision transformer backbone with channelwise cross-attention over patch tokens to create contextualized representations separately for each channel.
 
 
 ## Model Details
 
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+This model is a [channel-agnostic masked autoencoder](https://openaccess.thecvf.com/content/CVPR2024/html/Kraus_Masked_Autoencoders_for_Microscopy_are_Scalable_Learners_of_Cellular_Biology_CVPR_2024_paper.html) trained to reconstruct microscopy images over three datasets:
+1. RxRx3
+2. JUMP-CP overexpression
+3. JUMP-CP gene-knockouts
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
+- **Developed, funded, and shared by:** Recursion
+- **Model type:** Vision transformer CA-MAE
+- **Image modality:** Optimized for microscopy images from the CellPainting assay
 - **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
 
-<!-- Provide the basic links for the model. -->
+### Model Sources
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** [https://github.com/recursionpharma/maes_microscopy](https://github.com/recursionpharma/maes_microscopy)
+- **Paper:** [Masked Autoencoders for Microscopy are Scalable Learners of Cellular Biology](https://openaccess.thecvf.com/content/CVPR2024/html/Kraus_Masked_Autoencoders_for_Microscopy_are_Scalable_Learners_of_Cellular_Biology_CVPR_2024_paper.html)
 
 ## Uses