Update README.md

README.md

@@ -40,7 +40,7 @@ NOTE: model embeddings tend to extract features only after using standard batch
 
 ### Direct Use
 
-- Create biologically useful embeddings of microscopy images. We provide a [notebook](https://huggingface.co/recursionpharma/OpenPhenom/blob/main/RxRx3-core_inference.ipynb) for running inference on [RxRx3-core](https://huggingface.co/datasets/recursionpharma/rxrx3-core).
+- Create biologically useful embeddings of microscopy images
 - Create contextualized embeddings of each channel of a microscopy image (set `return_channelwise_embeddings=True`)
 - Leverage the full MAE encoder + decoder to predict new channels / stains for images without all 6 CellPainting channels
 
@@ -95,6 +95,7 @@ def test_model_predict(huggingface_model, C, return_channelwise_embeddings):
     expected_output_dim = 384 * C if return_channelwise_embeddings else 384
     assert embeddings.shape == (2, expected_output_dim)
 ```
+We also provide a [notebook](https://huggingface.co/recursionpharma/OpenPhenom/blob/main/RxRx3-core_inference.ipynb) for running inference on [RxRx3-core](https://huggingface.co/datasets/recursionpharma/rxrx3-core).
 
 **Note: Currently, the model cannot be loaded via the `AutoModel` available in HuggingFace transformers library**