NCP MEDIA / CONSULTING SERVICES
LLM Fine Tuning.
Adapt a language model to a defined task.
Explore whether a language model can be adapted to the behaviour your application needs. We assess the task, available examples and evaluation criteria before defining a fine-tuning project.
Built around your requirements.
The work begins with a baseline and a clear description of the outputs you want. We review whether the training data represents the task, prepare agreed datasets and plan evaluation on examples kept separate from training. Model choice and deployment constraints are assessed together. Fine-tuning is considered alongside prompting or retrieval when those approaches may better fit the requirement.
How we can help
- Use-case review and baseline definition
- Training and evaluation dataset preparation
- Fine-tuning experiments within an agreed scope
- Output evaluation and integration recommendations
From enquiry to a clear plan.
Share your requirements
Complete the service form with your goals, current setup and priorities.
Define the scope together
We review your request and discuss the work, dependencies and proposed approach.
Agree the next steps
Deliverables, timing and fees are agreed before the project starts.
LLM Fine Tuning
Tell us what you need.
Share a few details so our team can assess your request and discuss the next steps.
Useful details to include
Describe the task and the output you need, your current model if any, and the languages involved. Tell us what training examples exist and any deployment constraints. Please describe datasets without uploading confidential records.
Prefer email? info@ncp-media.com
Common questions.
Is fine-tuning the right starting point for every project?
No. We first assess the task and a baseline approach. Prompt design or retrieval may address the need; a fine-tuning project requires suitable examples and a way to evaluate the result.
What training data should we have?
Representative examples of the input and desired output are useful. Their suitability, consistency and permitted use need to be assessed before training. The required volume depends on the task and selected approach.