Generalist and Lightweight Model for Named Entity Recognition (Extract any entity types from texts) @ NAACL 2024
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Updated
Jul 16, 2024 - Python
Generalist and Lightweight Model for Named Entity Recognition (Extract any entity types from texts) @ NAACL 2024
An automated Hybrid Resume NER based on Rule-Based model, Machine Learning Model, and Transformer model
An elegent pytorch implement of transformers
A very simple framework for state-of-the-art Natural Language Processing (NLP)
modest natural-language processing
Insightful Tutorials and Papers about Knowledge Graphs
State of the Art Natural Language Processing
Build LLM-enabled FastAPI applications without build configuration.
1 line for thousands of State of The Art NLP models in hundreds of languages The fastest and most accurate way to solve text problems.
中文分词 词性标注 命名实体识别 依存句法分析 成分句法分析 语义依存分析 语义角色标注 指代消解 风格转换 语义相似度 新词发现 关键词短语提取 自动摘要 文本分类聚类 拼音简繁转换 自然语言处理
[EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and Construction
[OneKE] [ACL 2024] IEPile: A Large-Scale Information Extraction Corpus
USC CSCI544 - Applied Natural Language Processing - Fall 2023 - Prof Mohammad Rostami
AI assistant using Google TTS/STT, Keras, NLTK, Spacy, GPT-3, GPT-4, Hugging Face, Home Assistant, Spotify, and more.
💫 Industrial-strength Natural Language Processing (NLP) in Python
Legal document analysis using BERT
Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
🦙 Integrating LLMs into structured NLP pipelines
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