---
license: mit
pipeline_tag: mask-generation
tags:
- model_hub_mixin
- pytorch_model_hub_mixin
---

<!-- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
- 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)``` (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).

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]().

![](./figures/cifm.png)

## 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.
```
TBD
```