Implementation of Fast Transformer in Pytorch

Last update: Dec 27, 2022

Overview

Fast Transformer - Pytorch

Implementation of Fast Transformer in Pytorch. This only work as an encoder.

Install

$ pip install fast-transformer-pytorch

Usage

import torch
from fast_transformer_pytorch import FastTransformer

model = FastTransformer(
    num_tokens = 20000,
    dim = 512,
    depth = 2,
    max_seq_len = 4096,
    absolute_pos_emb = True   # default uses relative positional encoding, but if that isn't working, then turn on absolute positional embedding by setting this to True
)

x = torch.randint(0, 20000, (1, 4096))
mask = torch.ones(1, 4096).bool()

logits = model(x, mask = mask) # (1, 4096, 20000)

Citations

@misc{wu2021fastformer,
    title   = {Fastformer: Additive Attention is All You Need}, 
    author  = {Chuhan Wu and Fangzhao Wu and Tao Qi and Yongfeng Huang},
    year    = {2021},
    eprint  = {2108.09084},
    archivePrefix = {arXiv},
    primaryClass = {cs.CL}
}

A Transformer Implementation that is easy to understand and customizable.

Simple Transformer I've written a series of articles on the transformer architecture and language models on Medium. This repository contains an implem

4 Jan 20, 2022

Fast topic modeling platform

The state-of-the-art platform for topic modeling. Full Documentation User Mailing List Download Releases User survey What is BigARTM? BigARTM is a pow

633 Dec 21, 2022

Easy, fast, effective, and automatic g-code compression!

Getting to the meat of g-code. Easy, fast, effective, and automatic g-code compression! MeatPack nearly doubles the effective data rate of a standard

97 Nov 21, 2022

Library for fast text representation and classification.

fastText fastText is a library for efficient learning of word representations and sentence classification. Table of contents Resources Models Suppleme

24.1k Jan 5, 2023

💥 Fast State-of-the-Art Tokenizers optimized for Research and Production

Provides an implementation of today's most used tokenizers, with a focus on performance and versatility. Main features: Train new vocabularies and tok

6.2k Dec 31, 2022

✨Fast Coreference Resolution in spaCy with Neural Networks

✨ NeuralCoref 4.0: Coreference Resolution in spaCy with Neural Networks. NeuralCoref is a pipeline extension for spaCy 2.1+ which annotates and resolv

2.6k Jan 4, 2023

:house_with_garden: Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.

(Framework for Adapting Representation Models) What is it? FARM makes Transfer Learning with BERT & Co simple, fast and enterprise-ready. It's built u

1.6k Dec 27, 2022

Library for fast text representation and classification.

fastText fastText is a library for efficient learning of word representations and sentence classification. Table of contents Resources Models Suppleme

22.2k Feb 18, 2021

💥 Fast State-of-the-Art Tokenizers optimized for Research and Production

Provides an implementation of today's most used tokenizers, with a focus on performance and versatility. Main features: Train new vocabularies and tok

4.3k Feb 18, 2021

Releases(0.0.4)

0.0.4(Aug 25, 2021)

Source code(tar.gz)
Source code(zip)
0.0.3(Aug 24, 2021)

Source code(tar.gz)
Source code(zip)
0.0.2(Aug 23, 2021)

Source code(tar.gz)
Source code(zip)
0.0.1(Aug 23, 2021)

Source code(tar.gz)
Source code(zip)

Owner

Phil Wang

Working with Attention. It's all we need

GitHub Repository

Contains analysis of trends from Fitbit Dataset (source: Kaggle) to see how the trends can be applied to Bellabeat customers and Bellabeat products

Contains analysis of trends from Fitbit Dataset (source: Kaggle) to see how the trends can be applied to Bellabeat customers and Bellabeat products.

2 Jan 12, 2022

xFormers is a modular and field agnostic library to flexibly generate transformer architectures by interoperable and optimized building blocks.

Description xFormers is a modular and field agnostic library to flexibly generate transformer architectures by interoperable and optimized building bl

2.3k Jan 08, 2023

AMUSE - financial summarization

AMUSE AMUSE - financial summarization Unzip data.zip Train new model: python FinAnalyze.py --task train --start 0 --count how many files,-1 for all

1 Jan 11, 2022

Code associated with the "Data Augmentation using Pre-trained Transformer Models" paper

Data Augmentation using Pre-trained Transformer Models Code associated with the Data Augmentation using Pre-trained Transformer Models paper Code cont

44 Dec 31, 2022

Material for GW4SHM workshop, 16/03/2022.

GW4SHM Workshop Wednesday, 16th March 2022 (13:00 – 15:15 GMT): Presented by: Dr. Rhodri Nelson, Imperial College London Project website: https://www.

1 Mar 16, 2022

A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).

Splitter ⠀⠀ A PyTorch implementation of Splitter: Learning Node Representations that Capture Multiple Social Contexts (WWW 2019). Abstract Recent inte

201 Nov 09, 2022

PyTorch Implementation of the paper Single Image Texture Translation for Data Augmentation

SITT The repo contains official PyTorch Implementation of the paper Single Image Texture Translation for Data Augmentation. Authors: Boyi Li Yin Cui T

52 Jan 05, 2023

🌸 fastText + Bloom embeddings for compact, full-coverage vectors with spaCy

floret: fastText + Bloom embeddings for compact, full-coverage vectors with spaCy floret is an extended version of fastText that can produce word repr

222 Dec 16, 2022

An ultra fast tiny model for lane detection, using onnx_parser, TensorRTAPI, torch2trt to accelerate. our model support for int8, dynamic input and profiling. (Nvidia-Alibaba-TensoRT-hackathon2021)

Ultra_Fast_Lane_Detection_TensorRT An ultra fast tiny model for lane detection, using onnx_parser, TensorRTAPI to accelerate. our model support for in

121 Dec 27, 2022

AutoGluon: AutoML for Text, Image, and Tabular Data

AutoML for Text, Image, and Tabular Data AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in yo

5.2k Dec 29, 2022

Dense Passage Retriever - is a set of tools and models for open domain Q&A task.

Dense Passage Retrieval Dense Passage Retrieval (DPR) - is a set of tools and models for state-of-the-art open-domain Q&A research. It is based on the

1.1k Jan 07, 2023

基于“Seq2Seq+前缀树”的知识图谱问答

KgCLUE-bert4keras 基于“Seq2Seq+前缀树”的知识图谱问答简介博客：https://kexue.fm/archives/8802 环境软件：bert4keras=0.10.8 硬件：目前的结果是用一张Titan RTX（24G）跑出来的。运行第一次运行的时候，会给知

65 Dec 12, 2022

Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.

Pattern Pattern is a web mining module for Python. It has tools for: Data Mining: web services (Google, Twitter, Wikipedia), web crawler, HTML DOM par

8.4k Dec 30, 2022

Implementation of Fast Transformer in Pytorch

Related tags

Overview

Fast Transformer - Pytorch

Install

Usage

Citations

You might also like...

A Transformer Implementation that is easy to understand and customizable.

Fast topic modeling platform

Easy, fast, effective, and automatic g-code compression!

Library for fast text representation and classification.

💥 Fast State-of-the-Art Tokenizers optimized for Research and Production

✨Fast Coreference Resolution in spaCy with Neural Networks

:house_with_garden: Fast & easy transfer learning for NLP. Harvesting language models for the industry. Focus on Question Answering.

Library for fast text representation and classification.

💥 Fast State-of-the-Art Tokenizers optimized for Research and Production

Releases(0.0.4)

0.0.4(Aug 25, 2021)

0.0.3(Aug 24, 2021)

0.0.2(Aug 23, 2021)

0.0.1(Aug 23, 2021)

Owner

Phil Wang

Contains analysis of trends from Fitbit Dataset (source: Kaggle) to see how the trends can be applied to Bellabeat customers and Bellabeat products

xFormers is a modular and field agnostic library to flexibly generate transformer architectures by interoperable and optimized building blocks.

AMUSE - financial summarization

Code associated with the "Data Augmentation using Pre-trained Transformer Models" paper

Material for GW4SHM workshop, 16/03/2022.

A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).

PyTorch Implementation of the paper Single Image Texture Translation for Data Augmentation

🌸 fastText + Bloom embeddings for compact, full-coverage vectors with spaCy

An ultra fast tiny model for lane detection, using onnx_parser, TensorRTAPI, torch2trt to accelerate. our model support for int8, dynamic input and profiling. (Nvidia-Alibaba-TensoRT-hackathon2021)

AutoGluon: AutoML for Text, Image, and Tabular Data

Dense Passage Retriever - is a set of tools and models for open domain Q&A task.

基于“Seq2Seq+前缀树”的知识图谱问答

Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.

Machine translation models released by the Gourmet project

Converts python code into c++ by using OpenAI CODEX.

A simple implementation of N-gram language model.

Adversarial Examples for Extreme Multilabel Text Classification

nlp基础任务

Utilize Korean BERT model in sentence-transformers library

An easier way to build neural search on the cloud