Stars
SacreROUGE is a library dedicated to the use and development of text generation evaluation metrics with an emphasis on summarization.
Unsupervised text tokenizer focused on computational efficiency
curated collection of papers for the nlp practitioner 📖👩🔬
Giant Language Model Test Room
NAACL 2019 paper: Density Matching for Bilingual Word Embedding (Zhou et al., 2019)
📖 A collection of pure bash alternatives to external processes.
Codebase for testing whether hidden states of neural networks encode discrete structures.
With Holoviews, your data visualizes itself.
This dataset code generates mathematical question and answer pairs, from a range of question types at roughly school-level difficulty.
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk
A toolkit for evaluating the linguistic knowledge and transferability of contextual representations. Code for "Linguistic Knowledge and Transferability of Contextual Representations" (NAACL 2019).
Seamless operability between C++11 and Python
Papers from the computer science community to read and discuss.
Best practice and tips & tricks to write scientific papers in LaTeX, with figures generated in Python or Matlab.
Performs string manipulation tasks by learning from the provided example(s), instead of having to program them out explicitly.
🤖 My collection of highly opinionated and amazing configs
A general-purpose neural semantic parser for mapping natural language queries into machine executable code
An optimizer that trains as fast as Adam and as good as SGD.
Approximating Wasserstein distances with PyTorch
A PyTorch implementation of Mnemonic Reader for the Machine Comprehension task
Implementation of soft dynamic time warping in pytorch
📊 Save matplotlib figures as TikZ/PGFplots for smooth integration into LaTeX.
A full spaCy pipeline and models for scientific/biomedical documents.
official implementation for the paper "Simplifying Graph Convolutional Networks"