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+ ---
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+ license: apache-2.0
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+ inference: false
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+ ---
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+ # Enformer
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+ Enformer model. It was introduced in the paper [Effective gene expression prediction from sequence by integrating long-range interactions.](https://arxiv.org/abs/2010.11929) by Avsec et al. and first released in [this repository](https://github.com/deepmind/deepmind-research/tree/master/enformer).
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+ This repo contains the weights of the PyTorch implementation by Phil Wang as seen in the [enformer-pytorch repository](https://github.com/lucidrains/enformer-pytorch).
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+ Disclaimer: The team releasing Enformer did not write a model card for this model so this model card has been written by the Hugging Face team.
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+ ## Model description
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+ Enformer is a neural network architecture based on the Transformer that led to greatly increased accuracy in predicting gene expression from DNA sequence.
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+ We refer to the [paper](https://www.nature.com/articles/s41592-021-01252-x#citeas) published in Nature for details.
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+ ### How to use
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+ Refer to the README of [enformer-pyTorch](https://github.com/lucidrains/enformer-pytorch) regarding usage.
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+ ### Citation info
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+ ```
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+ Avsec, Ž., Agarwal, V., Visentin, D. et al. Effective gene expression prediction from sequence by integrating long-range interactions. Nat Methods 18, 1196–1203 (2021). https://doi.org/10.1038/s41592-021-01252-x
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+ ```