Language model Prompt And Query Archive

Related tags

Deep LearningLPAQA
Overview

LPAQA: Language model Prompt And Query Archive

This repository contains data and code for the paper How Can We Know What Language Models Know?

Install

Our repository is based on LAMA. Please download our fork from here and follow the instructions to set up the environment and download pre-trained language models.

# clone LPAQA
git clone https://github.com/jzbjyb/LPAQA.git LPAQA
# clone LAMA
git clone https://github.com/jzbjyb/LAMA.git LAMA
pushd LAMA && git reset --hard b6b1885c64de5981f249a8b65de25cb0802b4bd5 && rm -rf .git && popd
mv LAMA/* LPAQA/ && rm -rf LAMA
# follow the instructions to install
cd LPAQA
./setup.sh

Retrieve factual knowledge from LMs

For example, to query the owner of MSN (Microsoft is the answer), you can either use manually created prompts (x is owned by y):

python lama/eval_generation.py --lm bert --t "MSN is owned by [MASK]."

manual

or use LPAQA that ensembles a diversity of prompts:

# mined prompts
python lama/eval_ensemble.py --lm bert --subject MSN --relation P127 --prompts prompt/mine
# paraphrased prompts
python lama/eval_ensemble.py --lm bert --subject MSN --relation P127 --prompts prompt/paraphrase

mine

Owner
GitHub Repository
Goal of the project : Detecting Temporal Boundaries in Sign Language videos

MVA RecVis course final project : Goal of the project : Detecting Temporal Boundaries in Sign Language videos. Sign language automatic indexing is an

Loubna Ben Allal 6 Dec 21, 2022
Segmentation Training Pipeline

Segmentation Training Pipeline This package is a part of Musket ML framework. Reasons to use Segmentation Pipeline Segmentation Pipeline was developed

Musket ML 52 Dec 12, 2022
PyTorch implementation of Munchausen Reinforcement Learning based on DQN and SAC. Handles discrete and continuous action spaces

Exploring Munchausen Reinforcement Learning This is the project repository of my team in the "Advanced Deep Learning for Robotics" course at TUM. Our

Mohamed Amine Ketata 10 Mar 10, 2022
Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database.

MIMIC-III Benchmarks Python suite to construct benchmark machine learning datasets from the MIMIC-III clinical database. Currently, the benchmark data

Chengxi Zang 6 Jan 02, 2023
An index of recommendation algorithms that are based on Graph Neural Networks.

An index of recommendation algorithms that are based on Graph Neural Networks.

FIB LAB, Tsinghua University 564 Jan 07, 2023
Kaggle Ultrasound Nerve Segmentation competition [Keras]

Ultrasound nerve segmentation using Keras (1.0.7) Kaggle Ultrasound Nerve Segmentation competition [Keras] #Install (Ubuntu {14,16}, GPU) cuDNN requir

179 Dec 28, 2022
Official PyTorch implementation of SyntaSpeech (IJCAI 2022)

SyntaSpeech: Syntax-Aware Generative Adversarial Text-to-Speech | | | | 中文文档 This repository is the official PyTorch implementation of our IJCAI-2022

Zhenhui YE 116 Nov 24, 2022
A minimalist implementation of score-based diffusion model

sdeflow-light This is a minimalist codebase for training score-based diffusion models (supporting MNIST and CIFAR-10) used in the following paper "A V

Chin-Wei Huang 89 Dec 20, 2022
Balancing Principle for Unsupervised Domain Adaptation

Blancing Principle for Domain Adaptation NeurIPS 2021 Paper Abstract We address the unsolved algorithm design problem of choosing a justified regulari

Marius-Constantin Dinu 4 Dec 15, 2022
SOFT: Softmax-free Transformer with Linear Complexity, NeurIPS 2021 Spotlight

SOFT: Softmax-free Transformer with Linear Complexity SOFT: Softmax-free Transformer with Linear Complexity, Jiachen Lu, Jinghan Yao, Junge Zhang, Xia

Fudan Zhang Vision Group 272 Dec 25, 2022
Code for "Learning to Segment Rigid Motions from Two Frames".

rigidmask Code for "Learning to Segment Rigid Motions from Two Frames". ** This is a partial release with inference and evaluation code.

Gengshan Yang 157 Nov 21, 2022
LyaNet: A Lyapunov Framework for Training Neural ODEs

LyaNet: A Lyapunov Framework for Training Neural ODEs Provide the model type--config-name to train and test models configured as those shown in the pa

Ivan Dario Jimenez Rodriguez 21 Nov 21, 2022
Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network)

Deep Daze mist over green hills shattered plates on the grass cosmic love and attention a time traveler in the crowd life during the plague meditative

Phil Wang 4.4k Jan 03, 2023
Funnels: Exact maximum likelihood with dimensionality reduction.

Funnels This repository contains the code needed to reproduce the experiments from the paper: Funnels: Exact maximum likelihood with dimensionality re

2 Apr 21, 2022
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices

Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In

Trieu 6.1k Jan 04, 2023
Conceptual 12M is a dataset containing (image-URL, caption) pairs collected for vision-and-language pre-training.

Conceptual 12M We introduce the Conceptual 12M (CC12M), a dataset with ~12 million image-text pairs meant to be used for vision-and-language pre-train

Google Research Datasets 226 Dec 07, 2022
Pytorch Implementation of Value Retrieval with Arbitrary Queries for Form-like Documents.

Value Retrieval with Arbitrary Queries for Form-like Documents Introduction Pytorch Implementation of Value Retrieval with Arbitrary Queries for Form-

Salesforce 13 Sep 15, 2022
FlingBot: The Unreasonable Effectiveness of Dynamic Manipulations for Cloth Unfolding

This repository contains code for training and evaluating FlingBot in both simulation and real-world settings on a dual-UR5 robot arm setup for Ubuntu 18.04

Columbia Artificial Intelligence and Robotics Lab 70 Dec 06, 2022
A NSFW content filter.

Project_Nfilter A NSFW content filter. With a motive of minimizing the spreads and leakage of NSFW contents on internet and access to others devices ,

1 Jan 20, 2022
Code for the Higgs Boson Machine Learning Challenge organised by CERN & EPFL

A method to solve the Higgs boson challenge using Least Squares - Novae This project is the Project 1 of EPFL CS-433 Machine Learning. The project is

Giacomo Orsi 1 Nov 09, 2021