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What is llimba?

lballore/llimba — explained in plain English

Analysis updated 2026-05-18

3PythonAudience · researcherComplexity · 4/5LicenseSetup · moderate

In one sentence

An open-source AI language model fine-tuned to speak Sardinian, an endangered Romance language, small enough to run on a laptop or phone.

Mindmap

mindmap
  root((repo))
    What it does
      Sardinian conversation
      Text translation
      Endangered language AI
    Tech stack
      Python
      Qwen2.5
      Hugging Face
    Use cases
      Chat demo
      Translation
      Language research
    Audience
      Researchers
      Language learners

Code map

Detail Auto

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filefunction / class

What do people build with it?

USE CASE 1

Chat with an AI in Sardinian using the free browser demo.

USE CASE 2

Translate text between Sardinian and other Romance languages.

USE CASE 3

Study the model as a case study in low-resource language AI.

What is it built with?

PythonQwen2.5Hugging FacePyTorch

How does it compare?

lballore/llimba0marildo/imagoagentlexi/agent-lexi
Stars333
LanguagePythonPythonPython
Setup difficultymoderateeasymoderate
Complexity4/52/54/5
Audienceresearchergeneralvibe coder

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Running locally needs Python, the transformers library, and enough memory for a 3B parameter model, or use the free browser demo instead.

Use freely for any purpose, including commercial use, as long as you keep the copyright notice and state any changes made.

So what is it?

LLiMba (from LLM plus Limba, Sardinian for language) is an open-source project that trains an AI language model to speak Sardinian, a Romance language spoken in Sardinia, Italy that UNESCO classifies as endangered. Roughly 1 million people speak Sardinian, yet no major translation APIs or voice assistants support it. This project is a step toward changing that. The approach starts with an existing small multilingual model, 3 billion parameters, a measure of model size and capability, and adapts it for Sardinian through two rounds of training. First, the model reads around 13.9 million tokens of Sardinian text gathered from websites, Wikipedia, translated books, and poetry anthologies dating back to the 1400s. Then it is refined further on about 14,400 conversation pairs, teaching it to respond to questions and instructions in Sardinian. The resulting model can hold conversations, answer factual questions, and translate text between Sardinian and other languages. The model is designed to stay small: at its target compressed size of around 1.8 GB, it may run on a standard laptop or even a mobile device. All code, training data, and the model itself are published openly on Hugging Face under an Apache 2.0 license. A browser-based demo lets anyone try chatting with the model instantly, with no installation required. The project also compared several fine-tuning methods on the same data and hardware before settling on its final approach, and it published a technical report covering the data pipeline, training methodology, and findings. This would be useful to Sardinian language learners, researchers working on AI tools for minority or endangered languages, or developers building community services for Sardinian speakers.

Copy-paste prompts

Prompt 1
Help me run the LLiMba Sardinian model locally using the Hugging Face transformers pipeline.
Prompt 2
Explain how LLiMba was trained to speak Sardinian starting from a Qwen2.5 base model.
Prompt 3
Show me how to fine-tune a small multilingual model for an under-resourced language like LLiMba did.
Prompt 4
Walk me through LLiMba's data pipeline for collecting and cleaning Sardinian text.

Frequently asked questions

What is llimba?

An open-source AI language model fine-tuned to speak Sardinian, an endangered Romance language, small enough to run on a laptop or phone.

What language is llimba written in?

Mainly Python. The stack also includes Python, Qwen2.5, Hugging Face.

What license does llimba use?

Use freely for any purpose, including commercial use, as long as you keep the copyright notice and state any changes made.

How hard is llimba to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is llimba for?

Mainly researcher.

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