Project description

Progen

Implementation of Progen in Pytorch, from the paper "ProGen: Language Modeling for Protein Generation"

GPT for proteins sequences

Paper Link

Appreciation

Lucidrains
Agorians

Install

pip install progen-torch

Usage

from progen_torch import ProGen

x = torch.randint(0, 100, (1, 1024))
model = ProGenBase(num_tokens=100, dim=512, seq_len=1024, depth=6)
outputs = model(x)
print(outputs)

Architecture

Todo

License

MIT

Citations

Project details

These details have not been verified by PyPI

Project links

GitHub Statistics

View statistics for this project via Libraries.io, or by using our public dataset on Google BigQuery

Release history Release notifications | RSS feed

0.0.4

Oct 9, 2023

This version

0.0.3

Oct 9, 2023

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

progen_torch-0.0.3.tar.gz (6.8 kB view hashes)

Uploaded Oct 9, 2023 Source

Built Distribution

progen_torch-0.0.3-py3-none-any.whl (7.7 kB view hashes)

Uploaded Oct 9, 2023 Python 3

Hashes for progen_torch-0.0.3.tar.gz

Hashes for progen_torch-0.0.3.tar.gz
Algorithm	Hash digest
SHA256	`347af8fe56c372912e7c277d8835738187b0a05302784b6b993f857c9a4ce224`
MD5	`7cc2c9f363f0a43ebd20615f70101e94`
BLAKE2b-256	`39a636b14a16eec6fc702e452aa75776813eeae2b7ca6a396c854aa0bb4298b8`

Hashes for progen_torch-0.0.3-py3-none-any.whl

Hashes for progen_torch-0.0.3-py3-none-any.whl
Algorithm	Hash digest
SHA256	`3eb909f558a447640971ba23732f249a679d473bd20697a5d1ab92f8bb56ba8b`
MD5	`a023adeb9a2d953a7b27a6ae57846946`
BLAKE2b-256	`131fcb79ad36a0716b66a92e32afd179e5979e6defec7b7e21a81c058a2ba6c7`