Fine-tuning GPT for Direct Translations of an Old Indigenous Language - Seeking Advice

Hello fellow language enthusiasts and AI experts,

I am currently working on a project to fine-tune a GPT model for direct translations of an old indigenous language, specifically Mapudungun, which is spoken by the Mapuche people in Chile and Argentina. I am seeking advice on the best ways to create a dataset for fine-tuning and whether the available resources are sufficient for training the model.

I came across a dictionary available at the following URL, which provides translations between Mapudungun and Spanish:

My questions are:

  1. Is this dictionary sufficient to create a dataset for fine-tuning the GPT model, or do I need additional resources?
  2. What is the best approach to creating a high-quality dataset for training the model, considering the limited resources available for this language?
  3. Has anyone here worked on a similar project, or seen examples of fine-tuning GPT for direct translations of lesser-known or old indigenous languages? If so, please share your experiences and insights.

I appreciate any suggestions or guidance on this topic, as I believe that preserving and promoting the use of indigenous languages is of great cultural importance. I look forward to hearing from you and learning from your expertise.

Thank you in advance!

Did you get anywhere with this? I’d like to do similar with some languages that have several grammars and dictionaries available.

Mari mari peni, i have been also working on a model of mapuzugun! Chamultay peni!