The Adapter-Bot: All-In-One Controllable Conversational Model

Overview

The Adapter-Bot: All-In-One Controllable Conversational Model

This is the implementation of the paper: The Adapter-Bot: All-In-One Controllable Conversational Model. Zhaojiang Lin, Andrea Madotto, Yejin Bang, Pascale Fung AAAI-DEMO [PDF]

Citation:

If you find this paper and code useful, please cite our paper:

@article{madotto2020adapter,
  title={The Adapter-Bot: All-In-One Controllable Conversational Model},
  author={Madotto, Andrea and Lin, Zhaojiang and Bang, Yejin and Fung, Pascale},
  journal={arXiv preprint arXiv:2008.12579},
  year={2020}
}

Basic Installation

In this repository, we release the trained model, the knowledge retriever, and the interactive script (both via termial and the UI) of the adapter-bot.

Download models

To download the pretrained model run the following commands:

## pip install gdown
import gdown
import zipfile
import os


url = 'https://drive.google.com/uc?id=1JQZex-AD-sa5WUT5U4lIn1K2sPW-us8a/'
output = 'models.zip'
gdown.download(url, output, quiet=False)
with zipfile.ZipFile(output, 'r') as zip_ref:
    zip_ref.extractall()
os.remove(output)

Download and install knowledge retriever (KG and Wiki)

To download and install the knowledge retrievers you can have to follow the step in the retriever folder. Specifically, for the knowledge graph follow the read me at:

https://github.com/HLTCHKUST/adapterbot/tree/main/retriever/graphdb#installing-neo4j

which provides instructions to install neo4j and load opendialoKG. For the wikipedia knowledge, we use DrQA. Also in this case follow the read me at:

https://github.com/HLTCHKUST/adapterbot/tree/main/retriever/doc_ret

which provides a simple script for download the wikidump and train the tf-idf retriever.

Run the interactive script

To interact with the model via command line use the following script:

>>> python interact_adapter.py --interact
Owner
CAiRE
CAiRE
[NeurIPS 2021] The PyTorch implementation of paper "Self-Supervised Learning Disentangled Group Representation as Feature"

IP-IRM [NeurIPS 2021] The PyTorch implementation of paper "Self-Supervised Learning Disentangled Group Representation as Feature". Codes will be relea

Wang Tan 67 Dec 24, 2022
Boosting Adversarial Attacks with Enhanced Momentum (BMVC 2021)

EMI-FGSM This repository contains code to reproduce results from the paper: Boosting Adversarial Attacks with Enhanced Momentum (BMVC 2021) Xiaosen Wa

John Hopcroft Lab at HUST 10 Sep 26, 2022
An executor that performs image segmentation on fashion items

ClothingSegmenter U2NET fashion image/clothing segmenter based on https://github.com/levindabhi/cloth-segmentation Overview The ClothingSegmenter exec

Jina AI 5 Mar 30, 2022
Official implementation for the paper: Generating Smooth Pose Sequences for Diverse Human Motion Prediction

Generating Smooth Pose Sequences for Diverse Human Motion Prediction This is official implementation for the paper Generating Smooth Pose Sequences fo

Wei Mao 28 Dec 10, 2022
K-Nearest Neighbor in Pytorch

Pytorch KNN CUDA 2019/11/02 This repository will no longer be maintained as pytorch supports sort() and kthvalue on tensors. git clone https://github.

Chris Choy 65 Dec 01, 2022
Spectral Tensor Train Parameterization of Deep Learning Layers

Spectral Tensor Train Parameterization of Deep Learning Layers This repository is the official implementation of our AISTATS 2021 paper titled "Spectr

Anton Obukhov 12 Oct 23, 2022
HALO: A Skeleton-Driven Neural Occupancy Representation for Articulated Hands

HALO: A Skeleton-Driven Neural Occupancy Representation for Articulated Hands Oral Presentation, 3DV 2021 Korrawe Karunratanakul, Adrian Spurr, Zicong

Korrawe Karunratanakul 43 Oct 07, 2022
[CVPR 2022] "The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy" by Tianlong Chen, Zhenyu Zhang, Yu Cheng, Ahmed Awadallah, Zhangyang Wang

The Principle of Diversity: Training Stronger Vision Transformers Calls for Reducing All Levels of Redundancy Codes for this paper: [CVPR 2022] The Pr

VITA 16 Nov 26, 2022
Using LSTM write Tang poetry

本教程将通过一个示例对LSTM进行介绍。通过搭建训练LSTM网络,我们将训练一个模型来生成唐诗。本文将对该实现进行详尽的解释,并阐明此模型的工作方式和原因。并不需要过多专业知识,但是可能需要新手花一些时间来理解的模型训练的实际情况。为了节省时间,请尽量选择GPU进行训练。

56 Dec 15, 2022
An intelligent, flexible grammar of machine learning.

An english representation of machine learning. Modify what you want, let us handle the rest. Overview Nylon is a python library that lets you customiz

Palash Shah 79 Dec 02, 2022
Yolov5-opencv-cpp-python - Example of using ultralytics YOLO V5 with OpenCV 4.5.4, C++ and Python

yolov5-opencv-cpp-python Example of performing inference with ultralytics YOLO V

183 Jan 09, 2023
PyTorch implementation of the wavelet analysis from Torrence & Compo

Continuous Wavelet Transforms in PyTorch This is a PyTorch implementation for the wavelet analysis outlined in Torrence and Compo (BAMS, 1998). The co

Tom Runia 262 Dec 21, 2022
Anderson Acceleration for Deep Learning

Anderson Accelerated Deep Learning (AADL) AADL is a Python package that implements the Anderson acceleration to speed-up the training of deep learning

Oak Ridge National Laboratory 7 Nov 24, 2022
TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling

TiP-Adapter: Training-free CLIP-Adapter for Better Vision-Language Modeling This is the official code release for the paper 'TiP-Adapter: Training-fre

peng gao 189 Jan 04, 2023
dataset for ECCV 2020 "Motion Capture from Internet Videos"

Motion Capture from Internet Videos Motion Capture from Internet Videos Junting Dong*, Qing Shuai*, Yuanqing Zhang, Xian Liu, Xiaowei Zhou, Hujun Bao

ZJU3DV 98 Dec 07, 2022
Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach

Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach This is the implementation of traffic prediction code in DTMP based on PyTo

chenxin 1 Dec 19, 2021
A LiDAR point cloud cluster for panoptic segmentation

Divide-and-Merge-LiDAR-Panoptic-Cluster A demo video of our method with semantic prior: More information will be coming soon! As a PhD student, I don'

YimingZhao 65 Dec 22, 2022
This application explain how we can easily integrate Deepface framework with Python Django application

deepface_suite This application explain how we can easily integrate Deepface framework with Python Django application install redis cache install requ

Mohamed Naji Aboo 3 Apr 18, 2022
PyTorch implementation of Advantage async actor-critic Algorithms (A3C) in PyTorch

Advantage async actor-critic Algorithms (A3C) in PyTorch @inproceedings{mnih2016asynchronous, title={Asynchronous methods for deep reinforcement lea

LEI TAI 111 Dec 08, 2022
Code reproduce for paper "Vehicle Re-identification with Viewpoint-aware Metric Learning"

VANET Code reproduce for paper "Vehicle Re-identification with Viewpoint-aware Metric Learning" Introduction This is the implementation of article VAN

EMDATA-AILAB 23 Dec 26, 2022