LettuceDetect is a hallucination detection framework for RAG applications.

AdaSeq: An All-in-One Library for Developing State-of-the-Art Sequence Understanding Models

A Simple but Powerful SOTA NER Model | Official Code For Label Supervised LLaMA Finetuning

Transformer-based models implemented in tensorflow 2.x(using keras).

Code and data form the paper BERT Got a Date: Introducing Transformers to Temporal Tagging

Unofficial (Golang) Go bindings for the Hugging Face Inference API

A collection of datasets for Ukrainian language

Lightweight self-hosted span annotation tool

b站 AI日日新 不定期更新使用Python框架完成机器学习、深度学习、数据科学任务

Token classification using Phobert Models for Vietnamese

CNER: Concept and Named Entity Recognition

bullet: A Zero-Shot / Few-Shot Learning, LLM Based, text classification framework

The MERIT Dataset is a fully synthetic, labeled dataset created for training and benchmarking LLMs on Visually Rich Document Understanding tasks. It is also designed to help detect biases and improve interpretability in LLMs, where we are actively working. This repository is actively maintained, and new features are continuously being added.

A deep research study introducing the Gene Drift Hypothesis: a framework explaining how tokenomics mutate across market cycles. Analyzes evolutionary forces, selective pressures, behavioral traits, and economic genes that rise, fall, or mutate through bull/bear phases, shaping token species over time.

Applied Deep Learning 深度學習之應用 by Vivian Chen 陳縕儂 at NTU CSIE

A Java NLP application that identifies names, organizations, and locations in text by utilizing Hugging Face's RoBERTa NER model through the ONNX runtime and the Deep Java Library.

A research-grade framework for extracting, classifying, and analyzing the “genetic” behavior of smart contract tokens. Identifies economic traits, supply mutations, fee patterns, permission risks, upgradeability vectors, and scam species using a structured gene taxonomy with risk scoring, HTML reports, and token comparison tools.

Implementation of the paper, MAPLE - MAsking words to generate blackout Poetry using sequence-to-sequence LEarning, ICNLSP 2021

A research-grade exploration of the Tokenomics Ecological Framework, analyzing how tokens behave as predator, prey, parasite, and symbiotic species. Examines ecosystem interactions, evolutionary pressures, species population cycles, and the dynamics of economic predation, mutation, drift, and long-term survival across market cycles.

Data and code for the paper "ID10M: Idiom Identification in 10 Languages" (NAACL 2022).