Get started in minutes
Install the CLI and go from an empty directory to a deployed model in a few
minutes.
What you can do
Fine-tune a model on your own task
Write a TOML config, run one command, and Flash trains a LoRA adapter (a small set of add-on weights) on top of a supported base model. Pick the model and task; Flash handles the training infrastructure. See Training.Pick how the model learns
One line of config selects the algorithm. Use SFT when you already have example answers, GRPO when you can score an output but can’t hand-write the perfect one, and OPD when a stronger model already does the task and you want a small one to match it. See Training.Serve it behind an OpenAI-compatible API
flash models deploy registers the adapter with managed serving, then
flash models chat or any OpenAI client can call it with your Freesolo key. See
Deploy & chat.
See the cost before you spend
--cost prints the pre-flight estimate without starting a training run. You pay
for the quoted training run cost and for the tokens you serve. A cancelled run is
prorated from its quote by the share of the work it completed, never more. On an
SFT config the first --cost measures a separately billed workload profile
before it can quote. See Cost and billing.
Next steps
Quickstart
Install the CLI, log in, and ship your first run in a few minutes.
How Flash works
The loop behind a run: base models, environments, algorithms, serving.
Training
Write a config, submit a run, and follow it to completion.
Deploy & chat
Serve an adapter, then chat with it over an OpenAI-compatible API.