---
license: mit
library_name: pytorch-lightning
pipeline_tag: tabular-regression
tags:
- biology
- genomics
datasets:
- Genentech/borzoi-data
---

# Borzoi Model (Linder et al. 2025)

## Model Description
This repository contains the weights for the Borzoi model, a model designed to predict functional genomic tracks from genomic DNA sequences.

- **Architecture:** Convolutions followed by Transformer and U-net layers.
- **Input:** 524,288 bp of genomic DNA sequence.
- **Output Resolution:** 32 bp bins.
- **Source:** [Linder, J. et al. Nature Genetics (2025)](https://www.nature.com/articles/s41588-024-02053-6)


## Repository Content
The repository includes both full PyTorch Lightning checkpoints and raw state dictionaries for the human and mouse versions of the model. Each model has 4 independent replicates. Note that the weights are derived from the publication but the model has been converted into the PyTorch Lightning format used by gReLU (https://github.com/Genentech/gReLU).

| File | Type | Description |
| :--- | :--- | :--- |
| `human_rep0.ckpt` | PyTorch Lightning | Full checkpoint including base model and human head, replicate 0. |
| `human_rep1.ckpt` | PyTorch Lightning | Full checkpoint including base model and human head, replicate 1. |
| `human_rep2.ckpt` | PyTorch Lightning | Full checkpoint including base model and human head, replicate 2. |
| `human_rep3.ckpt` | PyTorch Lightning | Full checkpoint including base model and human head, replicate 3. |
| `mouse_rep0.ckpt` | PyTorch Lightning | Full checkpoint including base model and mouse head, replicate 0. |
| `mouse_rep1.ckpt` | PyTorch Lightning | Full checkpoint including base model and mouse head, replicate 1. |
| `mouse_rep2.ckpt` | PyTorch Lightning | Full checkpoint including base model and mouse head, replicate 2. |
| `mouse_rep3.ckpt` | PyTorch Lightning | Full checkpoint including base model and mouse head, replicate 3. |
| `human_state_dict_rep0.h5` | HDF5 | Weights-only state dictionary for the human model, replicate 0. |
| `human_state_dict_rep1.h5` | HDF5 | Weights-only state dictionary for the human model, replicate 1. |
| `human_state_dict_rep2.h5` | HDF5 | Weights-only state dictionary for the human model, replicate 2. |
| `human_state_dict_rep3.h5` | HDF5 | Weights-only state dictionary for the human model, replicate 3. |
| `mouse_state_dict_rep0.h5` | HDF5 | Weights-only state dictionary for the mouse model, replicate 0. |
| `mouse_state_dict_rep1.h5` | HDF5 | Weights-only state dictionary for the mouse model, replicate 1. |
| `mouse_state_dict_rep2.h5` | HDF5 | Weights-only state dictionary for the mouse model, replicate 2. |
| `mouse_state_dict_rep3.h5` | HDF5 | Weights-only state dictionary for the mouse model, replicate 3. |
| `save_wandb_borzoi_human.ipynb` | Jupyter Notebook | Code used to create human checkpoints |
| `save_wandb_borzoi_mouse.ipynb` | Jupyter Notebook | Code used to create mouse checkpoints |

## Model Heads & Output Tracks
The uman and mouse `.ckpt` files for the same replicate utilize the same core transformer trunk but differ in their species-specific output heads.

### Outputs

Human Head: 7,611 total tracks
Mouse Head: 2,608 total tracks

## Usage
The models are intended for use with the `grelu` library.

```python
from grelu.lightning import LightningModel
from huggingface_hub import hf_hub_download

# Download the desired checkpoint
ckpt_path = hf_hub_download(
    repo_id="Genentech/borzoi-model", 
    filename="human_rep0.ckpt"
)

# Load the model
model = LightningModel.load_from_checkpoint(ckpt_path)
model.eval()
```