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README.md

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 - pytorch_model_hub_mixin
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 - Library: ynyou/CIFM
-- Docs: [More Information Needed] -->
-
-# CI-FM: Cellular Interaction Foundation Model
-
-## 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)``` (the 1st Figure below panel D top);
-- **Inference/simulation** of cellular gene expressions within a certain microenvironment via ```expressions = model.predict_cells_at_locations(adata, target_locs)``` (the 1st Figure below panel D bottom, and the 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).
-
-More information about the model can be found in the [preprint](https://www.biorxiv.org/content/10.1101/2025.01.25.634867v1).
-
-![](./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.
-After entering the environment, you can clone the model via:
-```
-# Make sure you have git-lfs installed (https://git-lfs.com), e.g. as:
-git lfs install
-# or if you are under conda environment, you can also install git-lfs via conda as:
-conda install anaconda::git-lfs
-
-# clone the model and enter the directory
-git clone https://huggingface.co/ynyou/CIFM
-cd ./CIFM/
-git lfs install ; git lfs pull
-```
-
-The environment can be set up via:
-```
-# my python version is 3.11, which is manage when creating conda environment: conda create -n $MYENV python=3.11
-pip install torch==2.1.0 --index-url https://download.pytorch.org/whl/cu118
-pip install torch-scatter torch-sparse torch-cluster torch-geometric -f https://data.pyg.org/whl/torch-2.1.0+cu118.html
-pip install scanpy e3nn lightning==2.1.0 transformers numpy==1.26.4
-```
-where the compatibility between ```torch``` and ```torch-geometric``` is not always guaranteed (lines 2-3), since these two guys are very picky on the platform and the version of other packages. You may need trial-and-error to find the right versions of ```torch``` and ```torch-geometric``` that works for you, e.g., in some machine I once installed via:
-```
-pip install torch==2.0.1 --index-url https://download.pytorch.org/whl/cu117
-pip install torch-scatter torch-sparse torch-cluster torch-geometric -f https://data.pyg.org/whl/torch-2.0.1+cu117.html
-```
-
-## Citation
-If you use this code for you research, please cite our paper.
-```
-@article{you2025building,
-  title={Building Foundation Models to Characterize Cellular Interactions via Geometric Self-Supervised Learning on Spatial Genomics},
-  author={You, Yuning and Wang, Zitong and Fleisher, Kevin and Liu, Rex and Thomson, Matt},
-  journal={bioRxiv},
-  pages={2025--01},
-  year={2025},
-  publisher={Cold Spring Harbor Laboratory}
-}
-```
+- Docs: [More Information Needed]

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