Create README.md

README.md

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+---
+license: apache-2.0
+inference: false
+---
+
+# Enformer
+
+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). 
+
+This particular model was trained on sequences of 196,608 basepairs, target length 896, with shift augmentation but without reverse complement, on poisson loss objective. Final human pearson R of ~0.45.
+
+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).
+
+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.
+
+## Model description
+
+Enformer is a neural network architecture based on the Transformer that led to greatly increased accuracy in predicting gene expression from DNA sequence.
+
+We refer to the [paper](https://www.nature.com/articles/s41592-021-01252-x#citeas) published in Nature for details.
+
+### How to use
+
+Refer to the README of [enformer-pytorch](https://github.com/lucidrains/enformer-pytorch) regarding usage.
+
+
+### Citation info
+
+```
+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
+```