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Flair is a natural language processing framework for training and applying models for sequence labeling and text classification. It provides a system for generating word embeddings and identifying semantic entities within text. The framework includes a dedicated system for zero and few-shot learning, enabling text classification and entity extraction using minimal training examples by leveraging pre-trained knowledge. Its capabilities cover named entity recognition, sentiment analysis, and the training of specialized models using custom datasets. It also includes tooling for the visual highl
This project is a curated collection of Chinese names, surnames, and kinship terms designed for linguistic analysis and natural language processing. It functions as a multilingual name dataset and a training resource for named entity recognition, providing a unified repository of names across Chinese, Japanese, and English languages. The project includes a synthetic name generator that creates realistic person names by applying analyzed naming patterns and demographic data. It also provides a cleaned Chinese idiom lexicon gathered and deduplicated from multiple sources. The available data su
Flair is a transformer-based natural language processing framework used to build and train models for text classification and sequence tagging. It provides a specialized library for generating contextual text embeddings and performing linguistic analysis. The framework includes dedicated tools for named entity recognition, including the identification of specialized biomedical entities across multiple languages. It further supports entity linking to map identified text mentions to unique entries within general or biomedical knowledge bases. The project covers a broad range of language analys
llmware is a Python framework for AI agent orchestration and model management, designed to coordinate multi-model workflows and autonomous agents. It provides a unified model catalog and standardized interface to execute specialized language models for complex research, analysis, and structured data generation. The project distinguishes itself through its heavy emphasis on local execution and quantized inference, allowing models to run on private infrastructure using CPU, GPU, and NPU acceleration via runtimes like ONNX and OpenVino. It features a specialized ability to translate natural lang
The main features of hltcoe/golden-horse are: Entity Recognition and Segmentation, Multilingual Datasets, Named Entity Recognition.
Projects with overlapping indexed features include: wainshine/chinese-names-corpus — This project is a curated collection of Chinese names, surnames, and kinship terms designed for linguistic analysis… zalandoresearch/flair — Flair is a natural language processing framework for training and applying models for sequence labeling and text… flairnlp/flair — Flair is a transformer-based natural language processing framework used to build and train models for text… llmware-ai/llmware — llmware is a Python framework for AI agent orchestration and model management, designed to coordinate multi-model… arkhn/bio-nlp2023 — This project is the codebase used for our weak supervision experiments using E3C dataset annotated with InstructGPT-3… aliwazir/siner-dataset.