Stars
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
A very simple framework for state-of-the-art Natural Language Processing (NLP)
An open-source NLP research library, built on PyTorch.
The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.
Argilla is a collaboration tool for AI engineers and domain experts to build high-quality datasets
Pretrained language model with 100B parameters
Agent framework and applications built upon Qwen>=2.0, featuring Function Calling, Code Interpreter, RAG, and Chrome extension.
Beyond the Imitation Game collaborative benchmark for measuring and extrapolating the capabilities of language models
🚪✊Knock Knock: Get notified when your training ends with only two additional lines of code
A modular active learning framework for Python
NCRF++, a Neural Sequence Labeling Toolkit. Easy use to any sequence labeling tasks (e.g. NER, POS, Segmentation). It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components.
Super easy library for BERT based NLP models
brat rapid annotation tool (brat) - for all your textual annotation needs
🤖 A Python library for learning and evaluating knowledge graph embeddings
A collection of corpora for named entity recognition (NER) and entity recognition tasks. These annotated datasets cover a variety of languages, domains and entity types.
Fast and customizable framework for automatic ML model creation (AutoML)
LAMA - automatic model creation framework
ALiPy: Active Learning in Python is an active learning python toolbox, which allows users to conveniently evaluate, compare and analyze the performance of active learning methods.
The prime repository for state-of-the-art Multilingual Question Answering research and development.
A Comprehensive Framework for Building End-to-End Recommendation Systems with State-of-the-Art Models
Recommender system and evaluation framework for top-n recommendations tasks that respects polarity of feedbacks. Fast, flexible and easy to use. Written in python, boosted by scientific python stack.
A frame-semantic parsing system based on a softmax-margin SegRNN.