Protein Language Model

Overview

ProteinLM

We pretrain protein language model based on Megatron-LM framework, and then evaluate the pretrained model results on TAPE (Tasks Assessing Protein Embeddings), which contains a set of five biologically relevant semi-supervised learning tasks. And our pretrained model achieved good performance on these tasks.

Overview

The proposal of pre-training models such as Bert have greatly promoted the development of natural language processing, improving the performance of language models. Inspired by the similarity of amino acid sequence and text sequence, we consider applying the method of pre-training language model to biological data.

Guidance

We provide pretrain and finetune code in two separate folders. If you use the pretrained model we provide, you can simply download the checkpoint and follow the finetune guide. If you want to pretrain your own model yourself, you can refer to the pretrain guide.

Download ProteinLM

ProteinLM (200M)

For the pretrained model with 200 million parameters, you can download model checkpoint via GoogleDrive, or TsinghuaCloud.

ProteinLM (3B)

For the pretrained model with 3 billion parameters, you can download model checkpoint from here.

Project Structure

.
├── pretrain                (protein language model pretrain)
│   ├── megatron            (model folder)
│   ├── pretrain_tools      (multi-node pretrain)
│   ├── protein_tools       (data preprocess shells)
└── tape
    ├── conda_env           (conda env in yaml format)
    ├── converter           (converter script and model config files)
    ├── scripts             (model generator, finetune)
    └── tape                (tape model)

Usage

As the structure above shows, there are two stages as follows.

  • Pretrain
    • Prepare dataset (PFAM)
    • Preprocess data
    • Pretrain
  • Finetune
    • Convert pretrain protein model checkpoint
    • Finetune on downstream tasks

Detailed explanations are given in each folder's readme.

Downstream Tasks Performance

Task Metric TAPE ProteinLM (200M) ProteinLM (3B)
contact prediction [email protected]/5 0.36 0.52 0.75
remote homology Top 1 Accuracy 0.21 0.26 0.30
secondary structure Accuracy (3-class) 0.73 0.75 0.79
fluorescence Spearman's rho 0.68 0.68 0.68
stability Spearman's rho 0.73 0.77 0.79

Contact

If you have any problem using ProteinLM, feel free to contact us.

Reference

Our work is based on the following papers.

Besides, part of the code is based on Megatron-LM and TAPE.

Evaluating Protein Transfer Learning with TAPE

@article{DBLP:journals/corr/abs-1909-08053,
  author    = {Mohammad Shoeybi and
               Mostofa Patwary and
               Raul Puri and
               Patrick LeGresley and
               Jared Casper and
               Bryan Catanzaro},
  title     = {Megatron-LM: Training Multi-Billion Parameter Language Models Using
               Model Parallelism},
  journal   = {CoRR},
  volume    = {abs/1909.08053},
  year      = {2019},
  url       = {http://arxiv.org/abs/1909.08053},
  archivePrefix = {arXiv},
  eprint    = {1909.08053},
  timestamp = {Tue, 24 Sep 2019 11:33:51 +0200},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1909-08053.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

@article{DBLP:journals/corr/abs-1906-08230,
  author    = {Roshan Rao and
               Nicholas Bhattacharya and
               Neil Thomas and
               Yan Duan and
               Xi Chen and
               John F. Canny and
               Pieter Abbeel and
               Yun S. Song},
  title     = {Evaluating Protein Transfer Learning with {TAPE}},
  journal   = {CoRR},
  volume    = {abs/1906.08230},
  year      = {2019},
  url       = {http://arxiv.org/abs/1906.08230},
  archivePrefix = {arXiv},
  eprint    = {1906.08230},
  timestamp = {Sat, 23 Jan 2021 01:20:25 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-1906-08230.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
Owner
THUDM
Data Mining Research Group at Tsinghua University
THUDM
OpenChat: Opensource chatting framework for generative models

OpenChat is opensource chatting framework for generative models.

Hyunwoong Ko 427 Jan 06, 2023
[NeurIPS 2021] Code for Learning Signal-Agnostic Manifolds of Neural Fields

Learning Signal-Agnostic Manifolds of Neural Fields This is the uncleaned code for the paper Learning Signal-Agnostic Manifolds of Neural Fields. The

60 Dec 12, 2022
🕹 An esoteric language designed so that the program looks like the transcript of a Pokémon battle

PokéBattle is an esoteric language designed so that the program looks like the transcript of a Pokémon battle. Original inspiration and specification

Eduardo Correia 9 Jan 11, 2022
LSTM based Sentiment Classification using Tensorflow - Amazon Reviews Rating

LSTM based Sentiment Classification using Tensorflow - Amazon Reviews Rating (Dataset) The dataset is from Amazon Review Data (2018)

Immanuvel Prathap S 1 Jan 16, 2022
The source code of HeCo

HeCo This repo is for source code of KDD 2021 paper "Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning". Paper Link: htt

Nian Liu 106 Dec 27, 2022
sangha, pronounced "suhng-guh", is a social networking, booking platform where students and teachers can share their practice.

Flask React Project This is the backend for the Flask React project. Getting started Clone this repository (only this branch) git clone https://github

Courtney Newcomer 17 Sep 29, 2021
CMeEE 数据集医学实体抽取

医学实体抽取_GlobalPointer_torch 介绍 思想来自于苏神 GlobalPointer,原始版本是基于keras实现的,模型结构实现参考现有 pytorch 复现代码【感谢!】,基于torch百分百复现苏神原始效果。 数据集 中文医学命名实体数据集 点这里申请,很简单,共包含九类医学

85 Dec 28, 2022
Search-Engine - 📖 AI based search engine

Search Engine AI based search engine that was trained on 25000 samples, feel free to train on up to 1.2M sample from kaggle dataset, link below StackS

Vladislav Kruglikov 2 Nov 29, 2022
wxPython app for converting encodings, modifying and fixing SRT files

Subtitle Converter Program za obradu srt i txt fajlova. Requirements: Python version 3.8 wxPython version 4.1.0 or newer Libraries: srt, PyDispatcher

4 Nov 25, 2022
Convolutional 2D Knowledge Graph Embeddings resources

ConvE Convolutional 2D Knowledge Graph Embeddings resources. Paper: Convolutional 2D Knowledge Graph Embeddings Used in the paper, but do not use thes

Tim Dettmers 586 Dec 24, 2022
Include MelGAN, HifiGAN and Multiband-HifiGAN, maybe NHV in the future.

Fast (GAN Based Neural) Vocoder Chinese README Todo Submit demo Support NHV Discription Include MelGAN, HifiGAN and Multiband-HifiGAN, maybe include N

Zhengxi Liu (刘正曦) 134 Dec 16, 2022
Tool to check whether a GCP bucket is public or not.

Tool to check publicly accessible GCP bucket. Blog https://justm0rph3u5.medium.com/gcp-inspector-auditing-publicly-exposed-gcp-bucket-ac6cad55618c Wha

DIVYANSHU SHUKLA 7 Nov 24, 2022
Wake: Context-Sensitive Automatic Keyword Extraction Using Word2vec

Wake Wake: Context-Sensitive Automatic Keyword Extraction Using Word2vec Abstract استخراج خودکار کلمات کلیدی متون کوتاه فارسی با استفاده از word2vec ب

Omid Hajipoor 1 Dec 17, 2021
Implementation of Natural Language Code Search in the project CodeBERT: A Pre-Trained Model for Programming and Natural Languages.

CodeBERT-Implementation In this repo we have replicated the paper CodeBERT: A Pre-Trained Model for Programming and Natural Languages. We are interest

Tanuj Sur 4 Jul 01, 2022
Tool which allow you to detect and translate text.

Text detection and recognition This repository contains tool which allow to detect region with text and translate it one by one. Description Two pretr

Damian Panek 176 Nov 28, 2022
FactSumm: Factual Consistency Scorer for Abstractive Summarization

FactSumm: Factual Consistency Scorer for Abstractive Summarization FactSumm is a toolkit that scores Factualy Consistency for Abstract Summarization W

devfon 83 Jan 09, 2023
A Telegram bot to add notes to Flomo.

flomo bot 使用 Telegram 机器人发送笔记到你的 Flomo. 你需要有一台可访问 Telegram 的服务器。 Steps @BotFather 新建机器人,获取 token Flomo 官网获取 API,链接 https://flomoapp.com/mine?source=in

Zhen 44 Dec 30, 2022
Open-Source Toolkit for End-to-End Speech Recognition leveraging PyTorch-Lightning and Hydra.

OpenSpeech provides reference implementations of various ASR modeling papers and three languages recipe to perform tasks on automatic speech recogniti

Soohwan Kim 26 Dec 14, 2022
Smart discord chatbot integrated with Dialogflow

academic-NLP-chatbot Smart discord chatbot integrated with Dialogflow to interact with students naturally and manage different classes in a school. De

Tom Huynh 5 Oct 24, 2022
Dé op-de-vlucht Pieton vertaler. Wereldwijd gebruikt door meer dan 1.000+ succesvolle bedrijven!

Dé op-de-vlucht Pieton vertaler. Wereldwijd gebruikt door meer dan 1.000+ succesvolle bedrijven!

Lau 1 Dec 17, 2021