This PyTorch package implements MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation (NAACL 2022).

Related tags

Deep LearningMoEBERT
Overview

MoEBERT

This PyTorch package implements MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation (NAACL 2022).

Installation

  • Create and activate conda environment.
conda env create -f environment.yml
  • Install Transformers locally.
pip install -e .
  • Note: The code is adapted from this codebase. Arguments regarding LoRA and adapter can be safely ignored.

Instructions

MoEBERT targets task-specific distillation. Before running any distillation code, a pre-trained BERT model should be fine-tuned on the target task. Path to the fine-tuned model should be passed to --model_name_or_path.

Importance Score Computation

  • Use bert_base_mnli_example.sh to compute the importance scores, add a --preprocess_importance argument, remove the --do_train argument.
  • If multiple GPUs are used to compute the importance scores, a importance_[rank].pkl file will be saved for each GPU. Use merge_importance.py to merge these files.
  • To use the pre-computed importance scores, pass the file name to --moebert_load_importance.

Knowledge Distillation

  • For GLUE tasks, see examples/text-classification/run_glue.py.
  • For question answering tasks, see examples/question-answering/run_qa.py.
  • Run bash bert_base_mnli_example.sh as an example.
  • The codebase supports different routing strategies: gate-token, gate-sentence, hash-random and hash-balance. Choices should be passed to --moebert_route_method.
    • To use hash-balance, a balanced hash list needs to be pre-computed using hash_balance.py. Path to the saved hash list should be passed to --moebert_route_hash_list.
    • Add a load balancing loss by setting --moebert_load_balance when using trainable gating mechanisms.
    • The sentence-based gating mechanism (gate-sentence) is advantageous for inference because it induces significantly less communication overhead compared with token-level routing methods.
Owner
Simiao Zuo
PhD Student @ Georgia Tech
Simiao Zuo
Level Based Customer Segmentation

level_based_customer_segmentation Level Based Customer Segmentation Persona Veri Seti kullanılarak müşteri segmentasyonu yapılmıştır. KOLONLAR : PRICE

Buse Yıldırım 6 Dec 21, 2021
A library for implementing Decentralized Graph Neural Network algorithms.

decentralized-gnn A package for implementing and simulating decentralized Graph Neural Network algorithms for classification of peer-to-peer nodes. De

Multimedia Knowledge and Social Analytics Lab 5 Nov 07, 2022
Platform-agnostic AI Framework 🔥

🇬🇧 TensorLayerX is a multi-backend AI framework, which can run on almost all operation systems and AI hardwares, and support hybrid-framework progra

TensorLayer Community 171 Jan 06, 2023
Official implementation for CVPR 2021 paper: Adaptive Class Suppression Loss for Long-Tail Object Detection

Adaptive Class Suppression Loss for Long-Tail Object Detection This repo is the official implementation for CVPR 2021 paper: Adaptive Class Suppressio

CASIA-IVA-Lab 67 Dec 04, 2022
Film review classification

Film review classification Решение задачи классификации отзывов на фильмы на положительные и отрицательные с помощью рекуррентных нейронных сетей 1. З

Nikita Dukin 3 Jan 21, 2022
Compact Bidirectional Transformer for Image Captioning

Compact Bidirectional Transformer for Image Captioning Requirements Python 3.8 Pytorch 1.6 lmdb h5py tensorboardX Prepare Data Please use git clone --

YE Zhou 19 Dec 12, 2022
Pairwise Learning for Neural Link Prediction for OGB (PLNLP-OGB)

Pairwise Learning for Neural Link Prediction for OGB (PLNLP-OGB) This repository provides evaluation codes of PLNLP for OGB link property prediction t

Zhitao WANG 31 Oct 10, 2022
A two-stage U-Net for high-fidelity denoising of historical recordings

A two-stage U-Net for high-fidelity denoising of historical recordings Official repository of the paper (not submitted yet): E. Moliner and V. Välimäk

Eloi Moliner Juanpere 57 Jan 05, 2023
Nest - A flexible tool for building and sharing deep learning modules

Nest - A flexible tool for building and sharing deep learning modules Nest is a flexible deep learning module manager, which aims at encouraging code

ZhouYanzhao 41 Oct 10, 2022
Weakly- and Semi-Supervised Panoptic Segmentation (ECCV18)

Weakly- and Semi-Supervised Panoptic Segmentation by Qizhu Li*, Anurag Arnab*, Philip H.S. Torr This repository demonstrates the weakly supervised gro

Qizhu Li 159 Dec 20, 2022
Physics-informed Neural Operator for Learning Partial Differential Equation

PINO Physics-informed Neural Operator for Learning Partial Differential Equation Abstract: Machine learning methods have recently shown promise in sol

107 Jan 02, 2023
Code and results accompanying our paper titled Mixture Proportion Estimation and PU Learning: A Modern Approach at Neurips 2021 (Spotlight)

Mixture Proportion Estimation and PU Learning: A Modern Approach This repository is the official implementation of Mixture Proportion Estimation and P

Approximately Correct Machine Intelligence (ACMI) Lab 23 Dec 28, 2022
Source code for "MusCaps: Generating Captions for Music Audio" (IJCNN 2021)

MusCaps: Generating Captions for Music Audio Ilaria Manco1 2, Emmanouil Benetos1, Elio Quinton2, Gyorgy Fazekas1 1 Queen Mary University of London, 2

Ilaria Manco 57 Dec 07, 2022
[ICLR 2021] "CPT: Efficient Deep Neural Network Training via Cyclic Precision" by Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin

CPT: Efficient Deep Neural Network Training via Cyclic Precision Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin Accep

26 Oct 25, 2022
Single Image Super-Resolution (SISR) with SRResNet, EDSR and SRGAN

Single Image Super-Resolution (SISR) with SRResNet, EDSR and SRGAN Introduction Image super-resolution (SR) is the process of recovering high-resoluti

8 Apr 15, 2022
Fine-tune pretrained Convolutional Neural Networks with PyTorch

Fine-tune pretrained Convolutional Neural Networks with PyTorch. Features Gives access to the most popular CNN architectures pretrained on ImageNet. A

Alex Parinov 694 Nov 23, 2022
Chinese clinical named entity recognition using pre-trained BERT model

Chinese clinical named entity recognition (CNER) using pre-trained BERT model Introduction Code for paper Chinese clinical named entity recognition wi

Xiangyang Li 109 Dec 14, 2022
Dungeons and Dragons randomized content generator

Component based Dungeons and Dragons generator Supports Entity/Monster Generation NPC Generation Weapon Generation Encounter Generation Environment Ge

Zac 3 Dec 04, 2021
A whale detector design for the Kaggle whale-detector challenge!

CNN (InceptionV1) + STFT based Whale Detection Algorithm So, this repository is my PyTorch solution for the Kaggle whale-detection challenge. The obje

Tarin Ziyaee 92 Sep 28, 2021
PESTO: Switching Point based Dynamic and Relative Positional Encoding for Code-Mixed Languages

PESTO: Switching Point based Dynamic and Relative Positional Encoding for Code-Mixed Languages Abstract NLP applications for code-mixed (CM) or mix-li

Mohsin Ali, Mohammed 1 Nov 12, 2021