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.
brikerman/kashgari 的主要功能包括：Pre-trained Language Models, General NLP Toolkits, Python NLP Libraries。
brikerman/kashgari 的开源替代品包括： stanfordnlp/stanza — Stanza is a Python natural language processing library designed for tokenization, lemmatization, and dependency… huggingface/transformers — Transformers is a comprehensive library for machine learning that provides a unified interface for training,… chartbeat-labs/textacy — NLP, before and after spaCy. codertimo/bert-pytorch. huggingface/course — This project is an educational course and learning curriculum for implementing and fine-tuning transformer models… morvanzhou/tutorials — This repository is a comprehensive collection of instructional guides and practical examples for Python development,…
Stanza is a Python natural language processing library designed for tokenization, lemmatization, and dependency parsing across many human languages using neural models. It provides a neural processing pipeline that converts raw text into structured linguistic data objects, alongside a specialized analyzer for extracting medical insights from clinical and biomedical language. The project includes a wrapper that connects Python scripts to Java-based natural language processing tools and remote annotation servers. This enables a bridge for extracting linguistic annotations and analysis data from
Transformers is a comprehensive library for machine learning that provides a unified interface for training, fine-tuning, and deploying transformer-based models. It supports a wide range of tasks, including text classification, language modeling, question answering, and sequence-to-sequence translation, while offering specialized architectures for both text and vision processing. The framework includes tools for managing the entire model lifecycle, from data preprocessing and tokenization to distributed training and inference. The library features extensive support for model optimization and
