Python Bert-fine-tuning Resources

Expert-Linking Pytorch implementation of the paper "COAD: Contrastive Pre-training with Adversarial Fine-tuning for Zero-shot Expert Linking." This is

Graph-Bert Source code of "Graph-Bert: Only Attention is Needed for Learning Graph Representations". Please check the script.py as the entry point. We

G-Bert Pre-training of Graph Augmented Transformers for Medication Recommendation Intro G-Bert combined the power of Graph Neural Networks and BERT (B

Self-Guided Contrastive Learning for BERT Sentence Representations This repository is dedicated for releasing the implementation of the models utilize

Transformer-vocabulary-transfer Implementation of the paper "Fine-Tuning Transfo

ko-sentence-transformers 이 프로젝트는 KoBERT 모델을 sentence-transformers 에서 보다 쉽게 사용하기 위해 만들어졌습니다. Ko-Sentence-BERT-SKTBERT 프로젝트에서는 KoBERT 모델을 sentence-trans

🚨 Update 🚨 : As of 2021/10/17, the jiant project is no longer being actively maintained. This means there will be no plans to add new models, tasks,

PyBERT PyBERT is a serial communication link bit error rate tester simulator with a graphical user interface (GUI). It uses the Traits/UI package of t

Korean-Sentence-Embedding 🍭 Korean sentence embedding repository. You can download the pre-trained models and inference right away, also it provides

A Unified Framework for Parameter-Efficient Transfer Learning This is the official implementation of the paper: Towards a Unified View of Parameter-Ef

Prompt-Tuning Implementation of "The Power of Scale for Parameter-Efficient Prompt Tuning" Currently, we support the following huggigface models: Bart

BERT-of-Theseus Code for paper "BERT-of-Theseus: Compressing BERT by Progressive Module Replacing". BERT-of-Theseus is a new compressed BERT by progre

Robust fine-tuning of zero-shot models This repository contains code for the paper Robust fine-tuning of zero-shot models by Mitchell Wortsman*, Gabri

Sklearn-genetic-opt scikit-learn models hyperparameters tuning and feature selection, using evolutionary algorithms. This is meant to be an alternativ

BERT, LDA, and TFIDF based keyword extraction in Python kwx is a toolkit for multilingual keyword extraction based on Google's BERT and Latent Dirichl

BERT-based Financial Question Answering System In this example, we use Jina, PyTorch, and Hugging Face transformers to build a production-ready BERT-b

Fine-grained Post-training for Multi-turn Response Selection Implements the model described in the following paper Fine-grained Post-training for Impr

ruPrompts ruPrompts is a high-level yet extensible library for fast language model tuning via automatic prompt search, featuring integration with Hugg

Chinese named entity recognization (bert/roberta/macbert/bert_wwm with Keras)

Chinese NLP (albert/electra with Keras) Named Entity Recognization Project Structure ./ ├── NER │   ├── __init__.py │   ├── log

Label Studio for Hugging Face's Transformers Website • Docs • Twitter • Join Slack Community Transfer learning for NLP models by annotating your textu

English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models

The KLEJ Benchmark Baselines The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language und

ConvBERT Introduction In this repo, we introduce a new architecture ConvBERT for pre-training based language model. The code is tested on a V100 GPU.

Bort Companion code for the paper "Optimal Subarchitecture Extraction for BERT." Bort is an optimal subset of architectural parameters for the BERT ar

DeeBERT This is the code base for the paper DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference. Code in this repository is also available

DeBERTa: Decoding-enhanced BERT with Disentangled Attention This repository is the official implementation of DeBERTa: Decoding-enhanced BERT with Dis

ALBERT ***************New March 28, 2020 *************** Add a colab tutorial to run fine-tuning for GLUE datasets. ***************New January 7, 2020

💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab Notebooks. 🛫☑️

Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning Tensorflow code and models for the paper: Large Scale Fine-Grained Categ

Fine-grainedImageClassification Weakly Supervised Posture Mining with Reverse Cross-entropy for Fine-grained Classification We trained model here: lin

You can watch the details of the project on my youtube channel Project Interface Project Second Interface Goal= Correctly guessing the classification

Powerful unsupervised domain adaptation method for dense retrieval

Lime Comparing deep contextualized model for sentences highlighting task. In addition, take the classic explanation model "LIME" with bert-base model

AliceMind AliceMind: ALIbaba's Collection of Encoder-decoders from MinD (Machine IntelligeNce of Damo) Lab This repository provides pre-trained encode

MMO: Meta Multi-Objectivization for Software Configuration Tuning This repository contains the data and code for the following paper that is currently

Larch: Data Analysis Tools for X-ray Spectroscopy and More Documentation: http://xraypy.github.io/xraylarch Code: http://github.com/xraypy/xraylarch L

Image BERT Pre-Training with iBOT Official PyTorch implementation and pretrained models for paper iBOT: Image BERT Pre-Training with Online Tokenizer.

Introduction K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce. Installation PyTor

Class-Balanced Loss Based on Effective Number of Samples Tensorflow code for the paper: Class-Balanced Loss Based on Effective Number of Samples Yin C

Image BERT Pre-Training with iBOT Official PyTorch implementation and pretrained models for paper iBOT: Image BERT Pre-Training with Online Tokenizer.

AliceMind AliceMind: ALIbaba's Collection of Encoder-decoders from MinD (Machine IntelligeNce of Damo) Lab This repository provides pre-trained encode

DOP-Tuning DOP-Tuning(Domain-Oriented Prefix-tuning model)代码基于Prefix-Tuning改进. Files ├── seq2seq # Code for encoder-decoder arch

Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In

BERTMap: A BERT-based Ontology Alignment System Important Notices The relevant paper was accepted in AAAI-2022. Arxiv version is available at: https:/

PTR Code and datasets for our paper "PTR: Prompt Tuning with Rules for Text Classification" If you use the code, please cite the following paper: @art

Update: if you're looking for ColBERTv2 code, you can find it alongside a new simpler API, in the branch new_api. ColBERT ColBERT is a fast and accura

Fine-tuning wav2vec2 for speaker recognition This is the code used to run the experiments in https://arxiv.org/abs/2109.15053. Detailed logs of each t

AutoLRS This is the PyTorch code implementation for the paper AutoLRS: Automatic Learning-Rate Schedule by Bayesian Optimization on the Fly published

Pre-Training with Whole Word Masking for Chinese BERT

BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model

English|简体中文 ERNIE是百度开创性提出的基于知识增强的持续学习语义理解框架，该框架将大数据预训练与多源丰富知识相结合，通过持续学习技术，不断吸收海量文本数据中词汇、结构、语义等方面的知识，实现模型效果不断进化。ERNIE在累积 40 余个典型 NLP 任务取得 SOTA 效果，并在 G

This repository contains the resources in our paper "Revisiting Pre-trained Models for Chinese Natural Language Processing", which will be published i

K-BERT Sorce code and datasets for "K-BERT: Enabling Language Representation with Knowledge Graph", which is implemented based on the UER framework. R

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

VL-BERT By Weijie Su, Xizhou Zhu, Yue Cao, Bin Li, Lewei Lu, Furu Wei, Jifeng Dai. This repository is an official implementation of the paper VL-BERT:

TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation Zhaoyun Yin, Pichao Wang, Fan Wang, Xianzhe Xu, Hanling Zhang, Hao Li

TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation Zhaoyun Yin, Pichao Wang, Fan Wang, Xianzhe Xu, Hanling Zhang, Hao Li

Milano (This is a research project, not an official NVIDIA product.) Documentation https://nvidia.github.io/Milano Milano (Machine learning autotuner

BERTAC (BERT-style transformer-based language model with Adversarially pretrained Convolutional neural network) BERTAC is a framework that combines a

BERT Attention Analysis This repository contains code for What Does BERT Look At? An Analysis of BERT's Attention. It includes code for getting attent

BERT-Syntax Assesing the syntactic abilities of BERT. What Evaluate Google's BERT-Base and BERT-Large models on the syntactic agreement datasets from

Open Sesame This repository contains the code for the paper Open Sesame: Getting Inside BERT's Linguistic Knowledge. Credits We built the project on t

M-BERT-Study CROSS-LINGUAL ABILITY OF MULTILINGUAL BERT: AN EMPIRICAL STUDY Motivation Multilingual BERT (M-BERT) has shown surprising cross lingual a

Pretrained Transformers Improve Out-of-Distribution Robustness How does pretraining affect out-of-distribution robustness? We create an OOD benchmark

BERT-ATTACK Code for our EMNLP2020 long paper: BERT-ATTACK: Adversarial Attack Against BERT Using BERT Dependencies Python 3.7 PyTorch 1.4.0 transform

TextFooler A Model for Natural Language Attack on Text Classification and Inference This is the source code for the paper: Jin, Di, et al. "Is BERT Re

Are Sixteen Heads Really Better than One? This repository contains code to reproduce the experiments in our paper Are Sixteen Heads Really Better than

The Lottery Ticket Hypothesis for Pre-trained BERT Networks Code for this paper The Lottery Ticket Hypothesis for Pre-trained BERT Networks. [NeurIPS

When BERT Plays the Lottery, All Tickets Are Winning Large Transformer-based models were shown to be reducible to a smaller number of self-attention h

BERT is to NLP what AlexNet is to CV This is the official implementation of BERT is to NLP what AlexNet is to CV: Can Pre-Trained Language Models Iden

Introduction This repository is the code to reproduce the result of Efficient Training of BERT by Progressively Stacking. The code is based on Fairseq

EarlyBERT This is the official implementation for the paper in ACL-IJCNLP 2021 "EarlyBERT: Efficient BERT Training via Early-bird Lottery Tickets" by

Patience-based Early Exit Code for the paper "BERT Loses Patience: Fast and Robust Inference with Early Exit". NEWS: We now have a better and tidier i

ALBERT ***************New March 28, 2020 *************** Add a colab tutorial to run fine-tuning for GLUE datasets. ***************New January 7, 2020

This is the code for Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning It includes /bert, which is the original BERT repos

FastBERT Source code for "FastBERT: a Self-distilling BERT with Adaptive Inference Time". Good News 2021/10/29 - Code: Code of FastPLM is released on

DeeBERT This is the code base for the paper DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference. Code in this repository is also available

beyond-preserved-accuracy Repo for EMNLP 2021 paper "Beyond Preserved Accuracy: Evaluating Loyalty and Robustness of BERT Compression" How to implemen

Structured Super Lottery Tickets in BERT This repo contains our codes for the paper "Super Tickets in Pre-Trained Language Models: From Model Compress

Enabling Lightweight Fine-tuning for Pre-trained Language Model Compression based on Matrix Product Operators This is our Pytorch implementation for t

efficient-task-transfer This repository contains code for the experiments in our paper "What to Pre-Train on? Efficient Intermediate Task Selection".

New Release We released Adversarial training for both LM pre-training/finetuning and f-divergence. Large-scale Adversarial training for LMs: ALUM code

BERTGEN This repository is the implementation of the paper "BERTGEN: Multi-task Generation through BERT" (https://arxiv.org/abs/2106.03484). The codeb

Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks This repo contains the PyTorch implementation of the ACL, 2021 pa

PyTorch implementation of BERT and PALs Introduction Work by Asa Cooper Stickland and Iain Murray, University of Edinburgh. Code for BERT and PALs; mo

Adapter-BERT: Parameter-Efficient Transfer Learning for NLP.

LM-BFF (Better Few-shot Fine-tuning of Language Models) This is the implementation of the paper Making Pre-trained Language Models Better Few-shot Lea

EasyTransfer is designed to make the development of transfer learning in NLP applications easier. The literature has witnessed the success of applying

Information Gain Filtration Information Gain Filtration (IGF) is a method for filtering domain-specific data during language model finetuning. IGF sho

DominoSearch This is repository for codes and models of NeurIPS2021 paper - DominoSearch: Find layer-wise fine-grained N:M sparse schemes from dense n

Public code for NIPS submission "SimiGrad: Fine-Grained Adaptive Batching for Large Scale Training using Gradient Similarity Measurement" This repo co

Large-scale pre-trained language models (PLMs) such as BERT and GPT have achieved great success and become a milestone in NLP.

Search with BERT vectors in Solr and Elasticsearch

An Open Source Project from the Data to AI Lab, at MIT MLPrimitives Pipelines and primitives for machine learning and data science. Documentation: htt

FENSE The metric, Fluency ENhanced Sentence-bert Evaluation (FENSE), for audio caption evaluation, proposed in the paper "Can Audio Captions Be Evalua

Point-BERT: Pre-Training 3D Point Cloud Transformers with Masked Point Modeling Created by Xumin Yu*, Lulu Tang*, Yongming Rao*, Tiejun Huang, Jie Zho

Kazakh Named Entity Recognition This repository contains an open-source Kazakh named entity recognition dataset (KazNERD), named entity annotation gui

P-tuning v2 P-Tuning v2: Prompt Tuning Can Be Comparable to Finetuning Universally Across Scales and Tasks An optimized prompt tuning strategy achievi

Syne Tune This package provides state-of-the-art distributed hyperparameter optimizers (HPO) where trials can be evaluated with several backend option