ColBERT

ColBERT

Future Data Systems
+

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About

ColBERT is a fast and accurate retrieval model, enabling scalable BERT-based search over large text collections in tens of milliseconds. It relies on fine-grained contextual late interaction: it encodes each passage into a matrix of token-level embeddings. At search time, it embeds every query into another matrix and efficiently finds passages that contextually match the query using scalable vector-similarity (MaxSim) operators. These rich interactions allow ColBERT to surpass the quality of single-vector representation models while scaling efficiently to large corpora. The toolkit includes components for retrieval, reranking, evaluation, and response analysis, facilitating end-to-end workflows. ColBERT integrates with Pyserini for retrieval and provides integrated evaluation for multi-stage pipelines. It also includes a module for detailed analysis of input prompts and LLM responses, addressing reliability concerns with LLM APIs and non-deterministic behavior in Mixture-of-Experts.

About

Oracle SQL Developer is a free, integrated development environment that simplifies the development and management of Oracle Database in both traditional and Cloud deployments. SQL Developer offers complete end-to-end development of your PL/SQL applications, a worksheet for running queries and scripts, a DBA console for managing the database, a reports interface, a complete data modeling solution, and a migration platform for moving your 3rd party databases to Oracle. Run your sql and sql scripts, manage users, create and edit objects, import data to new or existing tables, diagnose performance issues, visualize your schemas, and much more. The power of your favorite desktop tool, in your browser. Available with Oracle REST Data Services for your on-premises instances. Migrate Oracle On-Premises to Oracle Cloud. Click, browse, and managed the contents of your Oracle Database.

About

fastText is an open source, free, and lightweight library developed by Facebook's AI Research (FAIR) lab for efficient learning of word representations and text classification. It supports both unsupervised learning of word vectors and supervised learning for text classification tasks. A key feature of fastText is its ability to capture subword information by representing words as bags of character n-grams, which enhances the handling of morphologically rich languages and out-of-vocabulary words. The library is optimized for performance and capable of training on large datasets quickly, and the resulting models can be reduced in size for deployment on mobile devices. Pre-trained word vectors are available for 157 languages, trained on Common Crawl and Wikipedia data, and can be downloaded for immediate use. fastText also offers aligned word vectors for 44 languages, facilitating cross-lingual natural language processing tasks.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Academic researchers and developers seeking a tool for implementing and evaluating listwise reranking with large language models

Audience

Developers in search of a database management solution to simplify the development and management of Oracle Database in both traditional and Cloud deployments

Audience

Language processing practitioners and researchers requiring a tool for learning word embeddings and building text classifiers

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 5.0 / 5
ease 3.0 / 5
features 4.0 / 5
design 3.0 / 5
support 4.0 / 5

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Future Data Systems
United States
github.com/stanford-futuredata/ColBERT

Company Information

Oracle
Founded: 1977
United States
www.oracle.com/database/technologies/appdev/sqldeveloper-landing.html

Company Information

fastText
fasttext.cc/

Alternatives

TILDE

TILDE

ielab

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Gensim

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RankLLM

RankLLM

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Aqua Data Studio

Aqua Data Studio

AquaFold, an Idera, Inc. company
GloVe

GloVe

Stanford NLP
RankGPT

RankGPT

Weiwei Sun
word2vec

word2vec

Google
BERT

BERT

Google
LexVec

LexVec

Alexandre Salle
RoBERTa

RoBERTa

Meta
SQLGate

SQLGate

CHEQUER

Categories

Categories

Categories

Integrations

BigID
C
C++
COBOL
Convertigo
Decube
Devart ODBC Drivers
Fortran
Java
JavaScript
Kiuwan Code Security
Oracle Cloud Infrastructure
Oracle Database
Oracle SQL Developer Data Modeler
Python
Qualis DMS
SEA Manager
SQL
SQLthroughAI
WebAssembly

Integrations

BigID
C
C++
COBOL
Convertigo
Decube
Devart ODBC Drivers
Fortran
Java
JavaScript
Kiuwan Code Security
Oracle Cloud Infrastructure
Oracle Database
Oracle SQL Developer Data Modeler
Python
Qualis DMS
SEA Manager
SQL
SQLthroughAI
WebAssembly

Integrations

BigID
C
C++
COBOL
Convertigo
Decube
Devart ODBC Drivers
Fortran
Java
JavaScript
Kiuwan Code Security
Oracle Cloud Infrastructure
Oracle Database
Oracle SQL Developer Data Modeler
Python
Qualis DMS
SEA Manager
SQL
SQLthroughAI
WebAssembly
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Claim ColBERT and update features and information
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