cedr | Contextualized Embeddings for Document Ranking | Machine Learning library

by Georgetown-IR-Lab Python Version: Current License: MIT

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kandi X-RAY | cedr Summary

cedr is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow, Bert applications. cedr has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Sean MacAvaney, Andrew Yates, Arman Cohan, Nazli Goharian. CEDR: Contextualized Embeddings for Document Ranking. SIGIR 2019 (short). tl;dr We demonstrate the effectiveness of using BERT classification for document ranking ("Vanilla BERT") and show that BERT embeddings can be used by prior neural ranking architectures to further improve ranking performance ("CEDR-* models"). If you use this work, please cite as: bibtex.

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cedr has a low active ecosystem.

It has 132 star(s) with 29 fork(s). There are 18 watchers for this library.

It had no major release in the last 6 months.

There are 8 open issues and 21 have been closed. On average issues are closed in 32 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of cedr is current.

Quality

cedr has 0 bugs and 0 code smells.

Security

cedr has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

cedr code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

cedr is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

cedr releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

cedr saves you 254 person hours of effort in developing the same functionality from scratch.

It has 617 lines of code, 51 functions and 8 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed cedr and discovered the below as its top functions. This is intended to give you an instant insight into cedr implemented functionality, and help decide if they suit your requirements.

Train the model
Train a single training iteration
Iterate over train pairs
Save the current state to a file
Read data files
Compute binary quadrature
Encode BERT
Get a subbatch of the given tokens
Unsubbatch embedding
Compute term matrix
Compute the relation between the given query
Read a dictionary from a tqdm file
Read qrels from file
Read a dictionary of pairs of pairs

Get all kandi verified functions for this library.

cedr Key Features

No Key Features are available at this moment for cedr.

cedr Examples and Code Snippets

No Code Snippets are available at this moment for cedr.

Community Discussions

Trending Discussions on cedr

How to split JSON data in Angular 2 and ionic 2

QUESTION

How to split JSON data in Angular 2 and ionic 2

Asked 2017-Jul-04 at 20:19

I need to separate the json file data, I create a function to separate the character string but it returns single strings:

"AKERMI ## 1988", "AKIM DE DUCOR ## 2005", ...

But I want to split this string into fields:

Name: AKERMI

Date: 1988

Name: AKIM DE DUCOR

Date: 2005

test.ts

...

ANSWER

Answered 2017-Jul-04 at 16:16

data.map(car => { 
let [name, year] = car.split('##');
return { name, year };
});

Source https://stackoverflow.com/questions/44908527

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install cedr

This code is tested on Python 3.6. Install dependencies using the following command:. You will need to prepare files for training and evaluation. Many of these files are available in data/wt (TREC WebTrack) and data/robust (TREC Robust 2004). qrels: a standard TREC-style query relevant file. Used for identifying relevant items for training pair generation and for validation (data/wt/qrels, data/robust/qrels).

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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