### **Training Process**
To train a tailored model:
1. **Create a Project**: Use the `/projects` endpoint to define your IP type and medium.
2. **Create a Dataset**: Use the `/datasets` endpoint to create a dataset within your project.
3. **Define Visual Identity**:
  - **Step A (Generate):** Call `/tailored-gen/generate_visual_schema`, sampling 5-10 images from your input set.
  - **Step B (Refine - Optional):** Call `/tailored-gen/refine_structured_prompt` with the generated schema and instructions to tweak the definitions (e.g., "Remove references to blue background").
  - **Step C (Apply):** Update the dataset with the final schema using `/datasets/{dataset_id}`.
4. **Upload Images**: Upload images using the `/datasets/{dataset_id}/images` or `/datasets/{dataset_id}/images/bulk` endpoints
(minimum resolution: 1024x1024px).
5. **Prepare Dataset**: Review auto-generated captions (you can also use `refine_structured_prompt` to fix specific image captions) and update the dataset status to 'completed'.
6. **Create Model**: Use the `/models` endpoint to create a model, which requires a training mode.
7. **Start Training**: Initiate training via the `/models/{id}/start_training` endpoint.
Training typically takes 4-6 hours.
8. **Monitor Progress**: Check the training status using the `/models/{id}` endpoint until
training is 'Completed'.
9. **Generate Images**:

- Use `v2/image/generate/tailored` for text-to-image generation.

Alternatively, manage and train tailored models through Bria's user-friendly Console.
Get started [here](https://platform.bria.ai/console/tailored-generation).