Update README.md

README.md

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-# maes_microscopy
+# Masked Autoencoders are Scalable Learners of Cellular Morphology
 Official repo for Recursion's accepted spotlight paper at NeurIPS 2023 Generative AI & Biology workshop.
+
+Paper: https://arxiv.org/abs/2309.16064
+
+![vit_diff_mask_ratios](https://github.com/recursionpharma/maes_microscopy/assets/109550980/409ac47b-a7d4-4158-b030-a88234e2b21f)
+
+## Provided code
+The baseline Vision Transformer architecture backbone used in this work can be built with the following code snippet from Timm:
+```
+import timm.models.vision_transformer as vit
+
+def vit_base_patch16_256(**kwargs):
+    default_kwargs = dict(
+        img_size=256,
+        in_chans=6,
+        num_classes=0,
+        fc_norm=None,
+        class_token=True,
+        drop_path_rate=0.1,
+        init_values=0.0001,
+        block_fn=vit.ParallelScalingBlock,
+        qkv_bias=False,
+        qk_norm=True,
+    )
+    for k, v in kwargs.items():
+        default_kwargs[k] = v
+    return vit.vit_base_patch16_224(**default_kwargs)
+```
+
+Additional code will be released as the date of the workshop gets closer.
+
+## Provided models
+Stay tuned...