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19 search results found

Uer Py ⭐ 2,802

Open Source Pre-training Model Framework in PyTorch & Pre-trained Model Zoo

Tencentpretrain ⭐ 951

Tencent Pre-training framework in PyTorch & Pre-trained Model Zoo

Question_generation ⭐ 836

Neural question generation using transformers

Transformers Tutorials ⭐ 777

Github repo with tutorials to fine tune transformers for diff NLP tasks

Keytotext ⭐ 418

Keywords to Sentences

⚡ boost inference speed of T5 models by 5x & reduce the model size by 3x.

Lm Question Generation ⭐ 207

Multilingual/multidomain question generation datasets, models, and python library for question generation.

Question_generator ⭐ 157

An NLP system for generating reading comprehension questions

Leaf Question Generation ⭐ 119

Easy to use and understand multiple-choice question generation algorithm using T5 Transformers.

PyTorch implementation and pre-trained models for ASP - Autoregressive Structured Prediction with Language Models, EMNLP 22. https://arxiv.org/pdf/2210.14698.pdf

Text2keywords ⭐ 54

Trained T5 and T5-large model for creating keywords from text

Awesome Llm ⭐ 53

Awesome series for Large Language Model(LLM)s

Dst As Prompting ⭐ 52

Source code for Dialogue State Tracking with a Language Modelusing Schema-Driven Prompting

Few Shot Lm ⭐ 40

The source code of "Language Models are Few-shot Multilingual Learners" (MRL @ EMNLP 2021)

Ratransformers ⭐ 38

RATransformers 🐭- Make your transformer (like BERT, RoBERTa, GPT-2 and T5) Relation Aware!

FTPipe and related pipeline model parallelism research.

Frame Semantic Transformer ⭐ 37

Frame Semantic Parser based on T5 and FrameNet

Johnsnowlabs ⭐ 35

Gateway into the John Snow Labs Ecosystem

A package for fine-tuning Transformers with TPUs, written in Tensorflow2.0+

User Simulation T5 ⭐ 30

Official Code for SIGIR 2022 "A Multi-task Based Neural Model to Simulate Users in Goal Oriented Dialogue Systems". User Simulator generates user-side utterance, predicts user's next action and satisfaction level.

Model Zoo ⭐ 29

NLP model zoo for Russian

Turkish Question Generation ⭐ 22

Automated question generation and question answering from Turkish texts using text-to-text transformers

Instructionner ⭐ 21

Unofficial implementation of paper "InstructionNER: A Multi-Task Instruction-Based Generative Framework for Few-shot NER" (https://arxiv.org/pdf/2203.03903v1.pdf)

T5 Japanese ⭐ 19

Codes to pre-train Japanese T5 models

Distilkobilstm ⭐ 17

Distilling Task-Specific Knowledge from Teacher Model into BiLSTM

Text-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Data

Text Summarizer ⭐ 16

Comparing state of the art models for text summary generation

Semeval2022 Task6 Sarcasm Detection ⭐ 11

Sarcasm is a term that refers to the use of words to mock, irritate, or amuse someone. It is commonly used on social media. The metaphorical and creative nature of sarcasm presents a significant difficulty for sentiment analysis systems based on affective computing. The technique and results of our team, UTNLP, in the SemEval-2022 shared task 6 on sarcasm detection are presented in this paper.

Academic Paper Title Recommendation ⭐ 9

Supervised text summarization (title generation/recommendation) based on academic paper abstracts, with Seq2Seq LSTM and the power of Transfer Learning and T5.

Lm Vocab Trimmer ⭐ 9

Vocabulary Trimming (VT) is a model compression technique, which reduces a multilingual LM vocabulary to a target language by deleting irrelevant tokens from its vocabulary. This repository contains a python-library vocabtrimmer, that remove irrelevant tokens from a multilingual LM vocabulary for the target language.

A full-text error corrector for English based on transformers and deep learning

JAX implementation of the T5 model: Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Text_normalization ⭐ 7

T5-based (russian) text normalization

[EMNLP 2023] FaMeSumm: Investigating and Improving Faithfulness of Medical Summarization. Support BART, PEGASUS, T5, mT5, BioBART, etc.

Domain Robustness Prompt Tuning ⭐ 6

Implementation of the report: on the domain robustness of prefix and prompt tuning

[제 11회 투빅스 컨퍼런스] AM I OK ? - 전문의 답변 기반 심리진단 AI

Audiolizr ⭐ 5

A bentoML-powered API to transcribe audio and make sense of it

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