It depends, and not every fine-tune makes you one: adapting a model in a limited way usually leaves you where you already were, as a deployer. What changes the answer is the scale of the modification, at which point provider obligations can attach in part. The role is settled by documenting the purpose of the fine-tuning, the dataset behind it and the distribution channel.
The trigger is not only technical. Under the EU AI Act you are treated as a provider, carrying the fuller obligation set, where you substantially modify a general-purpose model — or where you place the system on the market or put it into service under your own name or trademark. So branding and distribution choices can change your role as much as the training does. What settles it in practice is the scope of the fine-tuning, the compute and data behind it, whether the purpose of the model has changed, and how it is distributed. Allocate the consequences by contract while the role is still being fixed: who holds the technical documentation, who carries the copyright and personal-data compliance, and where the transparency duties sit. A role assigned wrongly leaves a compliance gap on one side of the line.
Shall we apply this matter to your situation?
Tell us your specific situation in a few sentences; we'll assess it with the right team.