
# Enformer

Enformer model. It was introduced in the paper [Effective gene expression prediction from sequence by integrating long-range interactions.](https://www.nature.com/articles/s41592-021-01252-x) 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 131,072 basepairs, target length 896 on v3-64 TPUs for 3 days with sequence augmentations and pearson correlation objective.

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) 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
```
{"license": "apache-2.0", "inference": false}
transformers pytorch enformer license:apache-2.0 region:us
TAGS
#transformers #pytorch #enformer #license-apache-2.0 #region-us 


# Enformer

Enformer model. It was introduced in the paper Effective gene expression prediction from sequence by integrating long-range interactions. by Avsec et al. and first released in this repository. 

This particular model was trained on sequences of 131,072 basepairs, target length 896 on v3-64 TPUs for 3 days with sequence augmentations and pearson correlation objective.

This repo contains the weights of the PyTorch implementation by Phil Wang as seen in the enformer-pytorch repository.

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 published in Nature for details.

### How to use

Refer to the README of enformer-pytorch regarding usage.


info


# Enformer

Enformer model. It was introduced in the paper Effective gene expression prediction from sequence by integrating long-range interactions. by Avsec et al. and first released in this repository. 

This particular model was trained on sequences of 131,072 basepairs, target length 896 on v3-64 TPUs for 3 days with sequence augmentations and pearson correlation objective.

This repo contains the weights of the PyTorch implementation by Phil Wang as seen in the enformer-pytorch repository.

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 published in Nature for details. ### How to use

Refer to the README of enformer-pytorch regarding usage.


info
TAGS
#transformers #pytorch #enformer #license-apache-2.0 #region-us 
 # Enformer

Enformer model. It was introduced in the paper Effective gene expression prediction from sequence by integrating long-range interactions. by Avsec et al. and first released in this repository. 

This particular model was trained on sequences of 131,072 basepairs, target length 896 on v3-64 TPUs for 3 days with sequence augmentations and pearson correlation objective.

This repo contains the weights of the PyTorch implementation by Phil Wang as seen in the enformer-pytorch repository.

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 published in Nature for details. ### How to use

Refer to the README of enformer-pytorch regarding usage.


info
passage: TAGS
#transformers #pytorch #enformer #license-apache-2.0 #region-us 
# Enformer

Enformer model. It was introduced in the paper Effective gene expression prediction from sequence by integrating long-range interactions. by Avsec et al. and first released in this repository. 

This particular model was trained on sequences of 131,072 basepairs, target length 896 on v3-64 TPUs for 3 days with sequence augmentations and pearson correlation objective.

This repo contains the weights of the PyTorch implementation by Phil Wang as seen in the enformer-pytorch repository.

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 published in Nature for details.### How to use

Refer to the README of enformer-pytorch regarding usage.


info