magiCARP: Contrastive Authoring+Reviewing Pretraining

Related tags

Deep LearningmagiCARP
Overview

magiCARP: Contrastive Authoring+Reviewing Pretraining

Welcome to the magiCARP API, the test bed used by EleutherAI for performing text/text bi-encoder experiments.

CARP, or contrastive authorship+reviewing pairings, was first outlined in Cut the CARP: Fishing for zero-shot story evaluation.

CARP presents a scalable method for performing zero-shot evaluation of stories and other mediums. Current CARP efforts at EleutherAI are primarily focused around controllable code generation. This repository will be updated with more experiments over the coming months as we try varying CARP architectures.

To train a model, run poetry run python -m carp.pytorch.train --data_path="carp/dataset" --config_path ./base_config.yml

Finetuning via COOP and preference learning coming soon.

Owner
EleutherAI
EleutherAI
Implementation for Learning to Track with Object Permanence

Learning to Track with Object Permanence A video-based MOT approach capable of tracking through full occlusions: Learning to Track with Object Permane

Toyota Research Institute - Machine Learning 91 Jan 03, 2023
Estimating Example Difficulty using Variance of Gradients

Estimating Example Difficulty using Variance of Gradients This repository contains source code necessary to reproduce some of the main results in the

Chirag Agarwal 48 Dec 26, 2022
FAMIE is a comprehensive and efficient active learning (AL) toolkit for multilingual information extraction (IE)

FAMIE: A Fast Active Learning Framework for Multilingual Information Extraction

18 Sep 01, 2022
MAVE: : A Product Dataset for Multi-source Attribute Value Extraction

MAVE: : A Product Dataset for Multi-source Attribute Value Extraction The dataset contains 3 million attribute-value annotations across 1257 unique ca

Google Research Datasets 89 Jan 08, 2023
Photographic Image Synthesis with Cascaded Refinement Networks - Pytorch Implementation

Photographic Image Synthesis with Cascaded Refinement Networks-Pytorch (https://arxiv.org/abs/1707.09405) This is a Pytorch implementation of cascaded

Soumya Tripathy 63 Mar 27, 2022
Generating synthetic mobility data for a realistic population with RNNs to improve utility and privacy

lbs-data Motivation Location data is collected from the public by private firms via mobile devices. Can this data also be used to serve the public goo

Alex 11 Sep 22, 2022
Users can free try their models on SIDD dataset based on this code

SIDD benchmark 1 Train python train.py If you want to train your network, just modify the yaml in the options folder. 2 Validation python validation.p

Yuzhi ZHAO 2 May 20, 2022
This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEECH" submitted to ICASSP 2022

CPC_DeepCluster This is the implementation of "SELF SUPERVISED REPRESENTATION LEARNING WITH DEEP CLUSTERING FOR ACOUSTIC UNIT DISCOVERY FROM RAW SPEEC

LEAP Lab 2 Sep 15, 2022
PyTorch Implementation of Unsupervised Depth Completion with Calibrated Backprojection Layers (ORAL, ICCV 2021)

Unsupervised Depth Completion with Calibrated Backprojection Layers PyTorch implementation of Unsupervised Depth Completion with Calibrated Backprojec

80 Dec 13, 2022
[CVPR 2022] Structured Sparse R-CNN for Direct Scene Graph Generation

Structured Sparse R-CNN for Direct Scene Graph Generation Our paper Structured Sparse R-CNN for Direct Scene Graph Generation has been accepted by CVP

Multimedia Computing Group, Nanjing University 44 Dec 23, 2022
TopFormer: Token Pyramid Transformer for Mobile Semantic Segmentation, CVPR2022

TopFormer: Token Pyramid Transformer for Mobile Semantic Segmentation Paper Links: TopFormer: Token Pyramid Transformer for Mobile Semantic Segmentati

Hust Visual Learning Team 253 Dec 21, 2022
This is the official implementation for the paper "Heterogeneous Multi-player Multi-armed Bandits: Closing the Gap and Generalization" in NeurIPS 2021.

MPMAB_BEACON This is code used for the paper "Decentralized Multi-player Multi-armed Bandits: Beyond Linear Reward Functions", Neurips 2021. Requireme

Cong Shen Research Group 0 Oct 26, 2021
R-package accompanying the paper "Dynamic Factor Model for Functional Time Series: Identification, Estimation, and Prediction"

dffm The goal of dffm is to provide functionality to apply the methods developed in the paper “Dynamic Factor Model for Functional Time Series: Identi

Sven Otto 3 Dec 09, 2022
Large scale embeddings on a single machine.

Marius Marius is a system under active development for training embeddings for large-scale graphs on a single machine. Training on large scale graphs

Marius 107 Jan 03, 2023
Demystifying How Self-Supervised Features Improve Training from Noisy Labels

Demystifying How Self-Supervised Features Improve Training from Noisy Labels This code is a PyTorch implementation of the paper "[Demystifying How Sel

<a href=[email protected]"> 4 Oct 14, 2022
Tensorflow2 Keras-based Semantic Segmentation Models Implementation

Tensorflow2 Keras-based Semantic Segmentation Models Implementation

Hah Min Lew 1 Feb 08, 2022
Project of 'TBEFN: A Two-branch Exposure-fusion Network for Low-light Image Enhancement '

TBEFN: A Two-branch Exposure-fusion Network for Low-light Image Enhancement Codes for TMM20 paper "TBEFN: A Two-branch Exposure-fusion Network for Low

KUN LU 31 Nov 06, 2022
Kohei's 5th place solution for xview3 challenge

xview3-kohei-solution Usage This repository assumes that the given data set is stored in the following locations: $ ls data/input/xview3/*.csv data/in

Kohei Ozaki 2 Jan 17, 2022
HyperDict - Self linked dictionary in Python

Hyper Dictionary Advanced python dictionary(hash-table), which can link it-self

8 Feb 06, 2022
Jittor implementation of PCT:Point Cloud Transformer

PCT: Point Cloud Transformer This is a Jittor implementation of PCT: Point Cloud Transformer.

MenghaoGuo 547 Jan 03, 2023