Product-Categorization-NLPMulti-Class Text Classification for products based on their description with Machine Learning algorithms and Neural Networks (MLP, CNN, Distilbert).
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policy-data-analyzerBuilding a model to recognize incentives for landscape restoration in environmental policies from Latin America, the US and India. Bringing NLP to the world of policy analysis through an extensible framework that includes scraping, preprocessing, active learning and text analysis pipelines.
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X-TransformerX-Transformer: Taming Pretrained Transformers for eXtreme Multi-label Text Classification
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kwxBERT, LDA, and TFIDF based keyword extraction in Python
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Lightnlp基于Pytorch和torchtext的自然语言处理深度学习框架。
Stars: ✭ 739 (+624.51%)
Spark NlpState of the Art Natural Language Processing
Stars: ✭ 2,518 (+2368.63%)
small-textActive Learning for Text Classification in Python
Stars: ✭ 241 (+136.27%)
TorchBlocksA PyTorch-based toolkit for natural language processing
Stars: ✭ 85 (-16.67%)
Pytorch-NLUPytorch-NLU,一个中文文本分类、序列标注工具包,支持中文长文本、短文本的多类、多标签分类任务,支持中文命名实体识别、词性标注、分词等序列标注任务。 Ptorch NLU, a Chinese text classification and sequence annotation toolkit, supports multi class and multi label classification tasks of Chinese long text and short text, and supports sequence annotation tasks such as Chinese named entity recognition, part of speech ta…
Stars: ✭ 151 (+48.04%)
SimpletransformersTransformers for Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI
Stars: ✭ 2,881 (+2724.51%)
Text mining resourcesResources for learning about Text Mining and Natural Language Processing
Stars: ✭ 358 (+250.98%)
keras-aquariuma small collection of models implemented in keras, including matrix factorization(recommendation system), topic modeling, text classification, etc. Runs on tensorflow.
Stars: ✭ 14 (-86.27%)
Sarcasm DetectionDetecting Sarcasm on Twitter using both traditonal machine learning and deep learning techniques.
Stars: ✭ 73 (-28.43%)
converseConversational text Analysis using various NLP techniques
Stars: ✭ 147 (+44.12%)
backpropBackprop makes it simple to use, finetune, and deploy state-of-the-art ML models.
Stars: ✭ 229 (+124.51%)
NSP-BERTThe code for our paper "NSP-BERT: A Prompt-based Zero-Shot Learner Through an Original Pre-training Task —— Next Sentence Prediction"
Stars: ✭ 166 (+62.75%)
10kGNADTen Thousand German News Articles Dataset for Topic Classification
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MetaLifelongLanguageRepository containing code for the paper "Meta-Learning with Sparse Experience Replay for Lifelong Language Learning".
Stars: ✭ 21 (-79.41%)
text2classMulti-class text categorization using state-of-the-art pre-trained contextualized language models, e.g. BERT
Stars: ✭ 15 (-85.29%)
MacadamMacadam是一个以Tensorflow(Keras)和bert4keras为基础,专注于文本分类、序列标注和关系抽取的自然语言处理工具包。支持RANDOM、WORD2VEC、FASTTEXT、BERT、ALBERT、ROBERTA、NEZHA、XLNET、ELECTRA、GPT-2等EMBEDDING嵌入; 支持FineTune、FastText、TextCNN、CharCNN、BiRNN、RCNN、DCNN、CRNN、DeepMoji、SelfAttention、HAN、Capsule等文本分类算法; 支持CRF、Bi-LSTM-CRF、CNN-LSTM、DGCNN、Bi-LSTM-LAN、Lattice-LSTM-Batch、MRC等序列标注算法。
Stars: ✭ 149 (+46.08%)
Marktool这是一款基于web的通用文本标注工具,支持大规模实体标注、关系标注、事件标注、文本分类、基于字典匹配和正则匹配的自动标注以及用于实现归一化的标准名标注,同时也支持文本的迭代标注和实体的嵌套标注。标注规范可自定义且同类型任务中可“一次创建多次复用”。通过分级实体集合扩大了实体类型的规模,并设计了全新高效的标注方式,提升了用户体验和标注效率。此外,本工具增加了审核环节,可对多人的标注结果进行一致性检验和调整,提高了标注语料的准确率和可靠性。
Stars: ✭ 190 (+86.27%)
Transformer-in-PyTorchTransformer/Transformer-XL/R-Transformer examples and explanations
Stars: ✭ 21 (-79.41%)
R-BERTPytorch re-implementation of R-BERT model
Stars: ✭ 59 (-42.16%)
question generatorAn NLP system for generating reading comprehension questions
Stars: ✭ 188 (+84.31%)
TextClassification基于scikit-learn实现对新浪新闻的文本分类,数据集为100w篇文档,总计10类,测试集与训练集1:1划分。分类算法采用SVM和Bayes,其中Bayes作为baseline。
Stars: ✭ 86 (-15.69%)
jax-modelsUnofficial JAX implementations of deep learning research papers
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CIANImplementation of the Character-level Intra Attention Network (CIAN) for Natural Language Inference (NLI) upon SNLI and MultiNLI corpus
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TransQuestTransformer based translation quality estimation
Stars: ✭ 85 (-16.67%)
stripnetSTriP Net: Semantic Similarity of Scientific Papers (S3P) Network
Stars: ✭ 82 (-19.61%)
teanaps자연어 처리와 텍스트 분석을 위한 오픈소스 파이썬 라이브러리 입니다.
Stars: ✭ 91 (-10.78%)
text analysis tools中文文本分析工具包(包括- 文本分类 - 文本聚类 - 文本相似性 - 关键词抽取 - 关键短语抽取 - 情感分析 - 文本纠错 - 文本摘要 - 主题关键词-同义词、近义词-事件三元组抽取)
Stars: ✭ 410 (+301.96%)
text gcn tutorialA tutorial & minimal example (8min on CPU) for Graph Convolutional Networks for Text Classification. AAAI 2019
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Transformer-MM-Explainability[ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.
Stars: ✭ 484 (+374.51%)
Nepali-News-ClassifierText Classification of Nepali Language Document. This Mini Project was done for the partial fulfillment of NLP Course : COMP 473.
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uniformer-pytorchImplementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification tasks, debuted in ICLR 2022
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ReQuestIndirect Supervision for Relation Extraction Using Question-Answer Pairs (WSDM'18)
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Text-Classification-LSTMs-PyTorchThe aim of this repository is to show a baseline model for text classification by implementing a LSTM-based model coded in PyTorch. In order to provide a better understanding of the model, it will be used a Tweets dataset provided by Kaggle.
Stars: ✭ 45 (-55.88%)
KnowledgeEditorCode for Editing Factual Knowledge in Language Models
Stars: ✭ 86 (-15.69%)
Att-BLSTM-relation-extractionImplementation of Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification.
Stars: ✭ 60 (-41.18%)
TOMA library for topic modeling and browsing
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bnpBayesian nonparametric models for python
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character-level-cnnKeras implementation of Character-level CNN for Text Classification
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score-zeroshotSemantically consistent regularizer for zero-shot learning
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STAM-pytorchImplementation of STAM (Space Time Attention Model), a pure and simple attention model that reaches SOTA for video classification
Stars: ✭ 109 (+6.86%)
clip-italianCLIP (Contrastive Language–Image Pre-training) for Italian
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spertPyTorch code for SpERT: Span-based Entity and Relation Transformer
Stars: ✭ 572 (+460.78%)