Projects sharing features with LLMAAA

CHisIEC: An Information Extraction Corpus for Ancient Chinese History

https://aclanthology.org/2023.emnlp-main.745.pdf

If you are just looking to download the LoRA weights directly, use this url: https://figshare.com/ndownloader/files/43044994 and view the data entry on Figshare.

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

FiftyOne is a visual tool for curating, analyzing, and managing image and video datasets for machine learning model training. It serves as a platform for identifying annotation errors, refining ground truth labels, and evaluating vision model performance by comparing predictions against ground truth to identify failure modes. The system functions as a containerized data platform that supports team collaboration on large-scale visual datasets in a cloud environment. It includes specialized capabilities for exploring high-dimensional embeddings to discover data clusters and retrieve correspondi

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

BioGPT is a biomedical large language model and domain-specific transformer designed for processing and creating specialized medical text. It functions as a generative tool and knowledge extraction engine trained on large-scale scientific literature to produce human-like scientific prose and factual responses to queries. The project provides specialized capabilities for biomedical named entity recognition and the extraction of complex relations from unstructured medical corpora. It is designed to identify and classify biological entities through data mining and relation extraction to support

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

Official code for ACL 2024 paper: VerifiNER: Verification-augmented NER via Knowledge-grounded Reasoning with Large Language Models.

This is the github repository for the paper to be appeared at NAACL 2024 main conference: Self-Improving for Zero-Shot Named Entity Recognition with Large Language Models.

This repository provides you with an easy-to-use labeling tool for State-of-the-art Deep Learning training purposes. It supports Auto-Labeling.

Code and prompt templates for evaluation-filtering Some data were not uploaded due to size restrictions, but you can find all the datasets covered in this paper by the references in the paper.

LLMs as Bridges: Reformulating Grounded Multimodal Named Entity Recognition

The codes and dataset will be released soon!

Read this in English. 本仓库基于LLaMA-Factory代码，实现了基于大语言模型的文档级关系抽取系统AutoRE。使用的抽取范式为RHF（论文链接）。 目前基于Re-DocRED数据集进行实验，能够抽取文档级文本中的96个关系的三元组事实。

Prompting ChatGPT in MNER: Enhanced Multimodal Named Entity Recognition with Auxiliary Refined Knowledge

Please save your dataset in data folder. Note that CoNLL2003 and WNUT2017 are open-source datasets, ACE2004 and ACE2005 are not free. We keep our CoNLL2003 and WNUT2017 train and test JSON files in data folder.

Dependencies are managed using Poetry. Use poetry install to install dependencies. You can then use poetry shell to obtain a shell with the created virtual environment activated.

Web labeling tool for bitmap images and point clouds

Code, data, and results described in the paper "Mining experimental data from materials science literature with large language models: an evaluation study", https://www.tandfonline.com/doi/full/10.1080/27660400.2024.2356506

Source code for AAAI 2022 paper: Unified Named Entity Recognition as Word-Word Relation Classification

Universal Information Extraction, codes for the NeurIPS-2022 paper: Unifying Information Extraction with Latent Adaptive Structure-aware Generative Language Model.