ARBML/nmatheg

A simple strategy for training and finetuning NLP models for Arabic. Specify the parameters and just wait for the results. A simple design that makes use of the different tools in our NLP pipeline.

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Experimental

This project helps people who need to train or fine-tune Natural Language Processing (NLP) models specifically for the Arabic language. You provide details like the dataset name (e.g., Arabic tweets or reviews) and desired training parameters, and it outputs a trained Arabic NLP model ready for various tasks. This is ideal for researchers, data scientists, or anyone working with Arabic text data who needs to develop custom NLP solutions without deep coding.

No commits in the last 6 months.

Use this if you have an Arabic text classification, named entity recognition, question answering, machine translation, or natural language inference problem and want a straightforward way to train or fine-tune a model.

Not ideal if your project involves languages other than Arabic or requires highly custom model architectures beyond common NLP tasks.

Arabic NLP text classification sentiment analysis named entity recognition machine translation
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 15 / 25

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21

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5

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Jupyter Notebook

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Category

arabic-nlp-tools

Last pushed

Jan 27, 2024

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