Shaw's repositories
FasterTransformer
Transformer related optimization, including BERT, GPT
AcademicShare191015
A document share for 学术新星计划2020分享会
KDD-2019-Hands-on
DGL tutorial in KDD 2019
PromptPapers
Must-read papers on prompt-based tuning for pre-trained language models.
REKCARC-TSC-UHT
清华大学计算机系课程攻略 Guidance for courses in Department of Computer Science and Technology, Tsinghua University
xiao9905.github.io
A beautiful, simple, clean, and responsive Jekyll theme for academics
awesome-bert
bert nlp papers, applications and github resources, including the newst xlnet ， BERT、XLNet 相关论文和 github 项目
awesome-graph-self-supervised-learning
Awesome Graph Self-Supervised Learning
awesome-self-supervised-gnn
Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).
awesome-self-supervised-learning
A curated list of awesome self-supervised methods
BIG-bench
Beyond the Imitation Game collaborative benchmark for measuring and extrapolating the capabilities of language models
causal-text-embeddings-1
Software and data for "Using Text Embeddings for Causal Inference"
COVID-19-TweetIDs
The repository contains an ongoing collection of tweets IDs associated with the novel coronavirus COVID-19 (SARS-CoV-2), which commenced on January 28, 2020.
gandissect
Pytorch-based tools for visualizing and understanding the neurons of a GAN. https://gandissect.csail.mit.edu/
GLM
GLM (General Language Model)
GLM-130B
GLM-130B: An Open Bilingual Pre-Trained Model
GraphMAE
GraphMAE: Self-supervised Masked Graph Autoencoders
interesting_causal_learning_papers
Collection of recent interesting papers related to causal inference from ICLR, NIPS, ICML
mips32-cpu
奋战一学期，造台计算机（编译出的bit文件在release中，可以直接食用）
P-tuning-v2
An optimized prompt tuning strategy comparable to fine-tuning across model scales and tasks.
promptsource
Toolkit for creating, sharing and using natural language prompts.
summarize-from-feedback
Code for "Learning to summarize from human feedback"
transformers
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.