#自然语言处理#Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.
翻译 - Kashgari是用于文本标签和文本分类的可立即投入生产的NLP Transfer学习框架,其中包括Word2Vec,BERT和GPT2语言嵌入。
#计算机科学#[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.
Entity and Relation Extraction Based on TensorFlow and BERT. 基于TensorFlow和BERT的管道式实体及关系抽取,2019语言与智能技术竞赛信息抽取任务解决方案。Schema based Knowledge Extraction, SKE 2019
#自然语言处理#This series will take you on a journey from the fundamentals of NLP and Computer Vision to the cutting edge of Vision-Language Models.
#自然语言处理#Trained models & code to predict toxic comments on all 3 Jigsaw Toxic Comment Challenges. Built using ⚡ Pytorch Lightning and 🤗 Transformers. For access to our API, please email us at contact@unitary...
#自然语言处理#Pre-training of Deep Bidirectional Transformers for Language Understanding: pre-train TextCNN
#自然语言处理#Portuguese pre-trained BERT models
#计算机科学#Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models
#自然语言处理#BlueBERT, pre-trained on PubMed abstracts and clinical notes (MIMIC-III).
#自然语言处理#A Model for Natural Language Attack on Text Classification and Inference
#自然语言处理#BETO - Spanish version of the BERT model
#自然语言处理#🤗 Pretrained BERT model & WordPiece tokenizer trained on Korean Comments 한국어 댓글로 프리트레이닝한 BERT 모델과 데이터셋
#自然语言处理#Abstractive summarisation using Bert as encoder and Transformer Decoder
#自然语言处理#BERT-NER (nert-bert) with google bert https://github.com/google-research.
#自然语言处理#End-to-End recipes for pre-training and fine-tuning BERT using Azure Machine Learning Service
#自然语言处理#Sentiment analysis neural network trained by fine-tuning BERT, ALBERT, or DistilBERT on the Stanford Sentiment Treebank.
Multiple-Relations-Extraction-Only-Look-Once. Just look at the sentence once and extract the multiple pairs of entities and their corresponding relations. 端到端联合多关系抽取模型,可用于 http://lic2019.ccf.org.cn/kg...
Semantics-aware BERT for Language Understanding (AAAI 2020)
Semantics-aware BERT for Language Understanding (AAAI 2020)