Large language model (LLM) fine-tuning
Fine-tuning specialises an open-source model in your field: your vocabulary, your style, your tasks. The result is a model you own and can host wherever you like.
Our fine-tuning process
Choosing the base model
An open-source model whose licence allows commercial use and modification.
Preparing the data
High-quality examples, built and checked with your experts.
Training and evaluation
GPU training, then tests on real cases before going live.
Deployment
The model runs on your machines or with a European host.
Real-world examples
- A legal model trained on French and Italian law for LegisBox.
- A model that writes technical reports in a company’s exact format.
- A model that sorts customer requests using an internal taxonomy.
Frequently asked questions
Fine-tuning or a RAG assistant: which one?
RAG brings up-to-date knowledge from your documents. Fine-tuning teaches the model a way of reasoning, writing or classifying. They are often combined.
How many examples are needed?
A few hundred carefully built examples are often enough for a specific task. Quality matters more than quantity.
Further reading
Articles to read
RAG or fine-tuning: how to specialise AI for your business
RAG gives AI access to your documents; fine-tuning changes the model itself.
AI and the GDPR: using artificial intelligence without exposing your data
As soon as an AI tool processes personal data, the GDPR applies.
Official sources and references
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Let’s talk about your project
A free first conversation, with no commitment, to see what would really help your business.