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README.md

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 ## Overview
 This is the PyTorch implementation of the CI-FM model -- an AI model that can simulate the activities within a living tissue (AI virtual tissue).
 The current version of CI-FM has 138M parameters and is trained on around 23M cells of spatial genomics. The signature functions of CI-FM are:
-- **Embedding** of celllular microenvironments via ```embeddings = model.embed(adata)``` (Figure below panel D top);
-- **Inference** of cellular gene expressions within a certain microenvironment via ```expressions = model.predict_cells_at_locations(adata, target_locs)``` (Figure below panel D bottom).
+- **Embedding** of celllular microenvironments via ```embeddings = model.embed(adata)``` (1st Figure below panel D top);
+- **Inference** of cellular gene expressions within a certain microenvironment via ```expressions = model.predict_cells_at_locations(adata, target_locs)``` (1st Figure below panel D bottom, and 2nd Figure below).
 
 The detailed usage of the model can be found in the [tutorial](https://huggingface.co/ynyou/CIFM/blob/main/test.ipynb).
 Before running the tutorial, please set up an environment following the [environment instruction](https://huggingface.co/ynyou/CIFM#environment).
@@ -24,6 +24,7 @@ Before running the tutorial, please set up an environment following the [environ
 More information about the model can be found in the [preprint]().
 
 ![](./figures/cifm.png)
+![](./figures/autoregressive.gif)
 
 ## Environment
 I use conda to manage the environment ```conda create -n $MYENV python=3.11```, but it is not the only way to do that.