Seedance 2.0 | Special Offer ✦ 10% OFF NOW | Ends May 13 (UTC+0)
Ana Sayfa/Keşfet/Pruna Ai/P Image/Text To Image Trainer

Pruna AI P-Image Text to Image Trainer API

pruna-ai /

Pruna AI P-Image Text to Image Trainer is a fast AI model training workflow for customizing text-to-image generation models with user-provided data. Ready-to-use REST inference API for training custom styles, brand-specific visuals, character concepts, product image generation, marketing creatives, and personalized AI image workflows with simple integration, no coldstarts, and affordable pricing.

training
Giriş

Sürükleyip bırakın veya yüklemek için tıklayın

Boşta

$1.8çalıştırma başına

İlgili Modeller

README

Pruna AI P-Image Text-to-Image Trainer

Pruna AI P-Image Text-to-Image Trainer is a fast training workflow for creating custom LoRAs for the Pruna text-to-image ecosystem. Upload your training image data, optionally provide a default caption, choose the number of training steps, and generate a LoRA that can be used to steer future image generation toward your style, subject, or brand look.

Why Choose This?

  • Fast custom LoRA training Train a text-to-image LoRA for specialized styles, subjects, or branded visuals.

  • Simple training interface Provide your training image data, optional default caption, and training steps without a complex setup process.

  • Optional caption guidance Use default_caption to provide consistent text conditioning across the training dataset.

  • Flexible training depth Use steps to balance speed, cost, and how strongly the LoRA learns your dataset.

  • Built for the Pruna image stack Trained outputs are intended for downstream use with Pruna text-to-image LoRA workflows.

  • Production-ready API Suitable for custom style pipelines, branded asset generation, and repeatable image workflow customization.

Parameters

ParameterRequiredDescription
image_dataYesTraining image data used to create the LoRA.
default_captionNoOptional default caption applied across the training workflow for more consistent conditioning.
stepsNoNumber of training steps. Higher values generally increase training time and cost. Default: 101.

How to Use

  1. Upload your training data — provide the image dataset you want to use for training.
  2. Add a default caption (optional) — use a short caption if you want more consistent text conditioning across the dataset.
  3. Set training steps — choose how many steps to run based on your desired balance of speed and training strength.
  4. Submit — start the training job.
  5. Use the trained LoRA — apply the resulting LoRA in downstream Pruna text-to-image LoRA workflows.

Example Workflow

Train a custom style LoRA from a curated image set, optionally using a shared default caption, then use the resulting weights in Pruna AI P-Image Text-to-Image LoRA for generation.

Pricing

Pricing is based on the selected steps value.

StepsCost
100$0.18
101$0.1818
250$0.45
500$0.90
1000$1.80
2000$3.60

Billing Rules

  • Pricing scales linearly with steps
  • Cost is $1.80 per 1,000 steps
  • Higher steps values increase total training cost proportionally
  • default_caption does not affect pricing

Best Use Cases

  • Custom style training — Create LoRAs for a distinct visual style or art direction.
  • Brand consistency — Train reusable LoRAs for campaigns, products, or branded aesthetics.
  • Subject-focused generation — Teach the model a recurring character, fashion look, or visual concept.
  • Creative workflow personalization — Build specialized LoRAs for repeatable prompt-driven generation.
  • Marketing asset pipelines — Create tailored generation tools for ongoing content production.

Pro Tips

  • Use a clean, consistent training dataset for better LoRA quality.
  • Add a default_caption when your dataset shares a common concept, subject, or style cue.
  • Start with a moderate number of steps before pushing to larger training runs.
  • Increase steps gradually if the initial LoRA is too weak or underfit.
  • Keep your dataset focused on the style or subject you want the LoRA to learn.
  • Test the trained LoRA in downstream generation workflows before scaling up training volume.

Notes

  • image_data is required.
  • default_caption is optional.
  • steps defaults to 101.
  • Pricing depends only on the selected steps value.
  • LoRAs trained here are intended for Pruna text-to-image LoRA usage.

Related Models

Erişilebilirlik:Bu web sitesi, üçüncü taraflarca sağlanan yapay zeka modellerini kullanmaktadır.