> ## Documentation Index
> Fetch the complete documentation index at: https://docs.seekr.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Fine-tuning

> Train models on your data with the SeekrFlow Python SDK.

For conceptual background on fine-tuning methods, training requirements, and when to use each approach, see [Fine-tuning](/flow/components/fine-tuning).

## Fine-tuning workflows

<CardGroup>
  <Card title="Create a fine-tuning job" icon="sparkles" href="/flow/sdk/fine-tuning/create-fine-tuning-job">
    Set up projects, configure training and infrastructure, and launch a fine-tuning job.
  </Card>

  <Card title="Reinforcement tuning" icon="sparkles" href="/flow/sdk/fine-tuning/grpo-fine-tuning">
    Train reasoning models with reward-based optimization using GRPO.
  </Card>

  <Card title="Preference tuning" icon="sparkles" href="/flow/sdk/fine-tuning/preference-tuning">
    Align model outputs with human preferences using DPO.
  </Card>

  <Card title="Vision language tuning" icon="sparkles" href="/flow/sdk/fine-tuning/vision-language-tuning">
    Fine-tune vision-language models on image-text datasets.
  </Card>

  <Card title="Low-rank adaptation" icon="sparkles" href="/flow/sdk/fine-tuning/lora">
    Apply low-rank adaptation to reduce training cost and memory usage.
  </Card>

  <Card title="Deploy a fine-tuned model" icon="rocket" href="/flow/sdk/fine-tuning/promote-a-fine-tuned-model">
    Promote models for inference, run chat completions, and manage deployments.
  </Card>
</CardGroup>