LiorSinai/TransformersLite.jl

A lightweight package for the transformer deep learning architecture in Julia

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Experimental

This package helps Julia programmers build custom deep learning models that understand context and generate sequences, like text or time series. It takes sequences of tokens (e.g., words represented as numbers) and produces classifications or new generated sequences based on transformer architecture components. This is ideal for machine learning engineers and researchers who need a lightweight, foundational toolkit for transformer-based applications.

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Use this if you are a Julia programmer who wants to build, learn about, or customize transformer models from basic building blocks rather than using a high-level API.

Not ideal if you need ready-to-use, production-grade transformer models with extensive pre-trained options or integrations with large model hubs like HuggingFace.

natural-language-processing machine-learning-engineering sequence-modeling deep-learning-research text-generation
No License Stale 6m No Package No Dependents
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Maturity 8 / 25
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Julia

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Last pushed

Mar 08, 2025

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