Indonlu

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IndoNLU is an open-source natural language processing benchmark for Indonesian Language. It provides 12 downstream tasks, pre-trained IndoBERT models, and starter code for researchers and developers.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Skill level

Technical

About

What is indonlu?

IndoNLU is a comprehensive collection of Natural Language Understanding (NLU) resources specifically designed for Bahasa Indonesia. It features 12 distinct downstream tasks, offering a robust benchmark for evaluating Indonesian language processing models. The project provides code to reproduce results and includes large pre-trained IndoBERT and IndoBERT-lite models, which were trained on an extensive 4-billion-word corpus (Indo4B) comprising over 20 GB of text data. Developed through a collaboration between universities and industry partners, IndoNLU also offers access to the Indo4B dataset and various FastText models. It serves as a vital resource for researchers and developers working on Indonesian NLP.

Best used for

Ideal for developers and data scientists who need to benchmark natural language understanding models, develop applications for the Indonesian language, and access pre-trained language models. Especially valuable for researchers and practitioners focusing on Indonesian NLP tasks and model evaluation.

Common actions

benchmark NLP models

develop Indonesian NLP

access language resources

train language models

workflowsdeepfakelow-code/no-codeopen-sourceautomated workflowcollaborationface swapping"AI Agents"github copilot

Capabilities

Key features

12 NLU tasks
Pre-trained IndoBERT models
Indo4B dataset access
FastText models
Starter code provided
Indonesian language benchmark

Target Audience

developerdata scientist

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What kind of tasks does IndoNLU support for Indonesian Natural Language Understanding?

IndoNLU supports 12 distinct downstream Natural Language Understanding (NLU) tasks for Bahasa Indonesia. These tasks are designed to provide a comprehensive benchmark for evaluating the performance of various NLP models on the Indonesian language.

Are there pre-trained models available with IndoNLU?

Yes, IndoNLU provides access to pre-trained IndoBERT and IndoBERT-lite models. These models were trained on a massive 4-billion-word corpus called Indo4B, offering robust language understanding capabilities for Indonesian.

How can I contribute to the IndoNLU project?

To contribute to IndoNLU, you should check the contributing guidelines provided in the repository. It's recommended to contact the maintainers or open an issue to gather feedback before submitting a pull request.

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