2 posts tagged with "fine-tuning"

FoundryDB now runs a complete AI stack on its own GPUs in Europe. You can serve open-weight models on a dedicated card in Helsinki behind an OpenAI-compatible endpoint, make those models the default for every AI surface in the platform, stop and start them so you are not renting an idle GPU, launch a RAG assistant from the marketplace that answers from your own documents with citations, and fine-tune a model on your own data and serve the result on the same endpoint. There is no external model vendor anywhere in that loop.

Managed Inference already gives you an open-weight LLM running on a dedicated EU GPU in Helsinki, served by vLLM behind an OpenAI-compatible endpoint, reached as foundrydb_managed/<model> with an fdb-inf key and wrapped in rate limits, token ceilings, EU residency, and GPU-hour metering. That is a great base model. It is not your model.

Today it can be. You can now serve your own LoRA fine-tuned adapters on that same managed GPU, live, with no restart. The base model stays loaded, your fine-tunes load alongside it, and each one answers on the same endpoint under the same governed controls. Your weights and your fine-tunes never leave EU infrastructure.