Stars
The TinyLlama project is an open endeavor to pretrain a 1.1B Llama model on 3 trillion tokens.
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
LibRerank is a toolkit for re-ranking algorithms. There are a number of re-ranking algorithms, such as PRM, DLCM, GSF, miDNN, SetRank, EGRerank, Seq2Slate.
Controllable Multi-Objective Re-ranking with Policy Hypernetworks (KDD 2023)
An open-source tool-augmented conversational language model from Fudan University
From Chain-of-Thought prompting to OpenAI o1 and DeepSeek-R1 🍓
Benchmarking large language models' complex reasoning ability with chain-of-thought prompting
Automatically exported from code.google.com/p/word2vec
Pytorch implementation of "A Probabilistic Formulation of Unsupervised Text Style Transfer" by He. et. al. at ICLR 2020
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
Optimus: the first large-scale pre-trained VAE language model
XTREME is a benchmark for the evaluation of the cross-lingual generalization ability of pre-trained multilingual models that covers 40 typologically diverse languages and includes nine tasks.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
DGMs for NLP. A roadmap.
Script that crawls meta data from ICLR OpenReview webpage. Tutorials on installing and using Selenium and ChromeDriver on Ubuntu.
A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems", which is `dmls-book`
Codes for <Kernelized Bayesian Softmax for Text Generation> in NeurIPS 2019
Data and Code for ICLR2020 Paper "TabFact: A Large-scale Dataset for Table-based Fact Verification"
AAAI-20 paper: Cross-Lingual Natural Language Generation via Pre-Training
Implementation of INLG 19 paper: Rethinking Text Attribute Transfer: A Lexical Analysis
Fast, general, and tested differentiable structured prediction in PyTorch
PyTorch implementation of A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text (EMNLP 2019)
Code examples for CMU CS11-731, Machine Translation and Sequence-to-sequence Models