P Image Edit Trainer

Pruna AI P-Image Edit Trainer

Pruna AI P-Image Edit Trainer is a fast training workflow for creating custom LoRAs for the Pruna image editing stack. Upload your training image data, choose the number of training steps, optionally provide a default caption, and generate a LoRA for downstream edit workflows such as style transfer, character-consistent edits, product edits, and other prompt-guided image editing tasks.

Why Choose This?

Fast custom edit LoRA training Train LoRAs specifically for image editing workflows rather than text-to-image generation.
Simple training interface Provide training image data and set training steps without a complex setup process.
Optional caption guidance Use default_caption to provide consistent text guidance across the training data.
Flexible training depth Adjust steps to balance speed, cost, and how strongly the LoRA learns your dataset.
Built for the Pruna edit stack Trained outputs are intended for downstream use with Pruna edit LoRA workflows.
Production-ready API Suitable for custom edit styles, character-consistent edits, branded asset pipelines, and repeatable editing workflows.

Parameters

Parameter	Required	Description
image_data	Yes	Training image data used to create the edit LoRA.
steps	No	Number of training steps. Higher values generally increase training time and cost. Default: `101`.
default_caption	No	Optional default caption applied to the training workflow for more consistent edit conditioning.

How to Use

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

Example Workflow

Train a custom edit LoRA for scene-to-scene style transfer, then use the resulting weights in Pruna AI P-Image Edit LoRA for guided image editing.

Pricing

Pricing is based on the selected steps value.

Steps	Cost
100	$0.40
101	$0.404
250	$1.00
500	$2.00
1000	$4.00
2000	$8.00

Billing Rules

Pricing scales linearly with steps
Cost is $4.00 per 1,000 steps
Higher steps values increase total training cost proportionally
default_caption does not affect pricing

Best Use Cases

Custom edit style training — create LoRAs for specific editing aesthetics or transformations
Character-consistent editing — train reusable LoRAs for recurring character edits
Product edit workflows — build LoRAs for consistent product transformations and asset updates
Brand asset editing — create custom edit models for repeatable branded visual workflows
Personalized image editing — train LoRAs tailored to a specific subject, look, or edit direction

Pro Tips

Use a clean, focused training dataset for better LoRA quality.
Start with a moderate number of steps before scaling to larger training runs.
Use default_caption when you want consistent conditioning across the dataset.
Keep the dataset aligned with the type of edits you want the LoRA to perform later.
Test the trained LoRA in downstream edit workflows before increasing training volume.

Notes

image_data is required.
steps defaults to 101.
default_caption is optional.
Pricing depends only on the selected steps value.
LoRAs trained here are intended for Pruna edit LoRA usage.
If you don't know the format, please see the official file: https://huggingface.co/datasets/davidberenstein1957/enhance/resolve/main/input.zip

Related Models

Pruna AI P-Image Edit LoRA — Edit images with prompt guidance and a trained edit LoRA.
Pruna AI P-Image Text-to-Image Trainer — Train LoRAs for text-to-image generation workflows.
Pruna AI P-Image Text-to-Image LoRA — Generate images from prompts using a trained LoRA.
Pruna AI P-Image Edit — Edit images with natural-language instructions without a LoRA.

P Image Edit Trainer API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/pruna-ai/p-image/edit-trainer with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for P Image Edit Trainer below.

HTTP example

# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/pruna-ai/p-image/edit-trainer" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d '{
    "steps": 101
}'

# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY"

# When status is "completed", read the output from data.outputs[0].

Node.js example

// npm install wavespeed
const WaveSpeed = require('wavespeed');

const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env

const result = await client.run("pruna-ai/p-image/edit-trainer", {
        "steps": 101
});

console.log(result.outputs[0]); // → URL of the generated output

Python example

# pip install wavespeed
import wavespeed

output = wavespeed.run(
    "pruna-ai/p-image/edit-trainer",
    {
    "steps": 101
}
)

print(output["outputs"][0])  # → URL of the generated output

P Image Edit Trainer API — Frequently asked questions

What is the P Image Edit Trainer API?

P Image Edit Trainer is a Pruna Ai model for AI inference, exposed as a REST API on WaveSpeedAI. Pruna AI P-Image Edit Trainer is a fast AI model training workflow for customizing image editing models with user-provided data. Ready-to-use REST inference API for training custom edit styles, character-consistent edits, product image updates, brand-specific visuals, marketing assets, and personalized AI image editing workflows with simple integration, no coldstarts, and affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the P Image Edit Trainer API?

POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/pruna-ai/pruna-ai-p-image-edit-trainer.

How much does P Image Edit Trainer cost per run?

P Image Edit Trainer starts at $4.00 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.

What inputs does P Image Edit Trainer accept?

Key inputs: `default_caption`, `image_data`, `steps`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/pruna-ai/pruna-ai-p-image-edit-trainer.

How do I get started with the P Image Edit Trainer API?

Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.

Can I use P Image Edit Trainer outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Pruna Ai). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

Related Models

README

Pruna AI P-Image Edit Trainer

Why Choose This?

Parameters

How to Use

Example Workflow

Pricing

Billing Rules

Best Use Cases

Pro Tips

Notes

Related Models

P Image Edit Trainer API — Quick start

P Image Edit Trainer API — Frequently asked questions