Use Tensorflow2.7.0 Build OpenAI'GPT-2

Overview

TF2_GPT-2

Use Tensorflow2.7.0 Build OpenAI'GPT-2 使用最新tensorflow2.7.0构建openai官方的GPT-2 NLP模型

优点

  • 使用无监督技术
  • 拥有大量词汇量
  • 可实现续写(堪比“xx梦续写”)
  • 实现对话后续将应用于FloatTech的Bot

食用方法

Setting

  • python >= 3.6
  • numpy==1.16.4
  • sentencepiece==0.1.83
  • tensorflow-gpu==2.7.0

Steps

1. git clone https://github.com/Xhs753/TF2_GPT-2
2. $ cd TF2_GPT-2
3. $ pip install -r requirments.txt

  • 你可以使用词仓库提供的sample.py示例数据预训练模型 ##### 对仓库的可用数据进行训练模型
$ pyton pre_process.py --help

可选项:
  --data-dir TEXT        训练数据路径  [默认: /data/scraped]
  --vocab-size INTEGER   词汇大小和字节大小  [默认: 24512]
  --min-seq-len INTEGER  最小词序长度  [默认: 15]
  --max-seq-len INTEGER  最大词序sequence长度  [默认: 512]
  --help                 显示所有信息并退出
  
  
 ==>>python pre_process.py

在任意数据上训练
>> python pre_process.py --data-dir=data_directory --vocab-size=32000

  • 有关模型的命令源码在此
@click.command()
@click.option('--num-layers', type=int, default=8, show_default=True, help="No. of decoder layers")
@click.option('--embedding-size', type=int, default=768, show_default=True, help="Embedding size")
@click.option('--num-heads', type=int, default=8, show_default=True, help="Number of heads")
@click.option('--dff', type=int, default=3072, show_default=True, help="Filter Size")
@click.option('--max-seq-len', type=int, default=515, show_default=True, help="Seq length")
@click.option('--vocab-size', type=int, default=24512, show_default=True, help="Vocab size")
@click.option('--optimizer', type=str, default="adam", show_default=True, help="optimizer type")
@click.option('--batch-size', type=int, default=8, show_default=True, help="optimizer type")
@click.option('--learning-rate', type=float, default=0.001, show_default=True, help="learning rate")
@click.option('--graph-mode', type=bool, default=False, show_default=False, help="TF run mode")
@click.option('--distributed', type=bool, default=False, show_default=False, help="distributed training")

####### 使用GPT-2

>> python train_gpt2.py \
  --num-layers=8 \
  --num-heads=8 \
  --dff=3072 \
  --embedding-size=768 \
  --batch-size=32 \
  --learning-rate=5e-5
  --graph-mode=True


模型架构

/image

Link

Thanks To My Friends

LICENCE

You might also like...
Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.

NeuroNER NeuroNER is a program that performs named-entity recognition (NER). Website: neuroner.com. This page gives step-by-step instructions to insta

When doing audio and video sentiment recognition, I found that a lot of code is duplicated, often a function in different time debugging for a long time, based on this problem, I want to manage all the previous work, organized into an open source library can be iterative. For their own use and others.
Easy to use, state-of-the-art Neural Machine Translation for 100+ languages

EasyNMT - Easy to use, state-of-the-art Neural Machine Translation This package provides easy to use, state-of-the-art machine translation for more th

🛸 Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy

spacy-transformers: Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy This package provides spaCy components and architectures to use tr

Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.

NeuroNER NeuroNER is a program that performs named-entity recognition (NER). Website: neuroner.com. This page gives step-by-step instructions to insta

🛸 Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy

spacy-transformers: Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy This package provides spaCy components and architectures to use tr

Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.

NeuroNER NeuroNER is a program that performs named-entity recognition (NER). Website: neuroner.com. This page gives step-by-step instructions to insta

Code to use Augmented Shapiro Wilks Stopping, as well as code for the paper "Statistically Signifigant Stopping of Neural Network Training"

This codebase is being actively maintained, please create and issue if you have issues using it Basics All data files are included under losses and ea

A collection of Korean Text Datasets ready to use using Tensorflow-Datasets.

tfds-korean A collection of Korean Text Datasets ready to use using Tensorflow-Datasets. TensorFlow-Datasets를 이용한 한국어/한글 데이터셋 모음입니다. Dataset Catalog |

Releases(GPT-2)
Owner
Watermelon
(-^〇^-) A cute watermelon 🍉
Watermelon
One Stop Anomaly Shop: Anomaly detection using two-phase approach: (a) pre-labeling using statistics, Natural Language Processing and static rules; (b) anomaly scoring using supervised and unsupervised machine learning.

One Stop Anomaly Shop (OSAS) Quick start guide Step 1: Get/build the docker image Option 1: Use precompiled image (might not reflect latest changes):

Adobe, Inc. 148 Dec 26, 2022
Espresso: A Fast End-to-End Neural Speech Recognition Toolkit

Espresso Espresso is an open-source, modular, extensible end-to-end neural automatic speech recognition (ASR) toolkit based on the deep learning libra

Yiming Wang 919 Jan 03, 2023
मराठी भाषा वाचविण्याचा एक प्रयास. इंग्रजी ते मराठीचा शब्दकोश. An attempt to preserve the Marathi language. A lightweight and ad free English to Marathi thesaurus.

For English, scroll down मराठी शब्द मराठी भाषा वाचवण्यासाठी मी हा ओपन सोर्स प्रोजेक्ट सुरू केला आहे. माझ्या मते, आपली भाषा हळूहळू आणि कोणाचाही लक्षात

मुक्त स्त्रोत 20 Oct 11, 2022
Repo for Enhanced Seq2Seq Autoencoder via Contrastive Learning for Abstractive Text Summarization

ESACL: Enhanced Seq2Seq Autoencoder via Contrastive Learning for AbstractiveText Summarization This repo is for our paper "Enhanced Seq2Seq Autoencode

Rachel Zheng 14 Nov 01, 2022
Live Speech Portraits: Real-Time Photorealistic Talking-Head Animation (SIGGRAPH Asia 2021)

Live Speech Portraits: Real-Time Photorealistic Talking-Head Animation This repository contains the implementation of the following paper: Live Speech

OldSix 575 Dec 31, 2022
FedNLP: A Benchmarking Framework for Federated Learning in Natural Language Processing

FedNLP is a research-oriented benchmarking framework for advancing federated learning (FL) in natural language processing (NLP). It uses FedML repository as the git submodule. In other words, FedNLP

FedML-AI 216 Nov 27, 2022
中文問句產生器;使用台達電閱讀理解資料集(DRCD)

Transformer QG on DRCD The inputs of the model refers to we integrate C and A into a new C' in the following form. C' = [c1, c2, ..., [HL], a1, ..., a

Philip 1 Oct 22, 2021
Implementation for paper BLEU: a Method for Automatic Evaluation of Machine Translation

BLEU Score Implementation for paper: BLEU: a Method for Automatic Evaluation of Machine Translation Author: Ba Ngoc from ProtonX BLEU score is a popul

Ngoc Nguyen Ba 6 Oct 07, 2021
Repositório da disciplina no semestre 2021-2

Avisos! Nenhum aviso! Compiladores 1 Este é o Git da disciplina Compiladores 1. Aqui ficará o material produzido em sala de aula assim como tarefas, w

6 May 13, 2022
This is the writeup of all the challenges from Advent-of-cyber-2019 of TryHackMe

Advent-of-cyber-2019-writeup This is the writeup of all the challenges from Advent-of-cyber-2019 of TryHackMe https://tryhackme.com/shivam007/badges/c

shivam danawale 5 Jul 17, 2022
An official implementation for "CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval"

The implementation of paper CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval. CLIP4Clip is a video-text retrieval model based

ArrowLuo 456 Jan 06, 2023
This project converts your human voice input to its text transcript and to an automated voice too.

Human Voice to Automated Voice & Text Introduction: In this project, whenever you'll speak, it will turn your voice into a robot voice and furthermore

Hassan Shahzad 3 Oct 15, 2021
A Streamlit web app that generates Rick and Morty stories using GPT2.

Rick and Morty Story Generator This project uses a pre-trained GPT2 model, which was fine-tuned on Rick and Morty transcripts, to generate new stories

₸ornike 33 Oct 13, 2022
Machine learning models from Singapore's NLP research community

SG-NLP Machine learning models from Singapore's natural language processing (NLP) research community. sgnlp is a Python package that allows you to eas

AI Singapore | AI Makerspace 21 Dec 17, 2022
Code for "Parallel Instance Query Network for Named Entity Recognition", accepted at ACL 2022.

README Code for Two-stage Identifier: "Parallel Instance Query Network for Named Entity Recognition", accepted at ACL 2022. For details of the model a

Yongliang Shen 45 Nov 29, 2022
This is an incredibly powerful calculator that is capable of many useful day-to-day functions.

Description 💻 This is an incredibly powerful calculator that is capable of many useful day-to-day functions. Such functions include solving basic ari

Jordan Leich 37 Nov 19, 2022
A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks

A Deep Learning NLP/NLU library by Intel® AI Lab Overview | Models | Installation | Examples | Documentation | Tutorials | Contributing NLP Architect

Intel Labs 2.9k Jan 02, 2023
CATs: Semantic Correspondence with Transformers

CATs: Semantic Correspondence with Transformers For more information, check out the paper on [arXiv]. Training with different backbones and evaluation

74 Dec 10, 2021
Phrase-BERT: Improved Phrase Embeddings from BERT with an Application to Corpus Exploration

Phrase-BERT: Improved Phrase Embeddings from BERT with an Application to Corpus Exploration This is the official repository for the EMNLP 2021 long pa

70 Dec 11, 2022