p-image-edit-lora
P-Image Edit LoRA combines the speed and quality of P-Image Edit with the flexibility of Low-Rank Adaptation (LoRA) fine-tuning. This enables custom style transfer, character consistency, brand-specific aesthetics, and domain-specific edits using pre-trained LoRA weights from HuggingFace. The model maintains sub-second inference while applying custom adaptations, making it ideal for production workflows requiring consistent styling or specialized editing capabilities.
api_example.sh
Technical Specifications
Model Architecture & Performance
Pricing
Pay-per-use, no commitments
API Reference
Complete parameter documentation
| Parameter | Type | Default | Description |
|---|---|---|---|
| lora_weights | string | null | HuggingFace URL to LoRA weights. Supports public and private repositories (requires hf_api_token for private). |
| lora_scale | number | 1 | Controls the strength of LoRA application. Values: -1.0 to 3.0. Higher values apply stronger LoRA effects. Default: 1.0 |
| hf_api_token | string | null | HuggingFace API token for accessing private LoRA weights. Required only for private repositories. |
| turbo | boolean | true | Enable faster optimizations for quicker inference. Recommended to keep enabled for production use. |
| aspect_ratio | string | 16:9 | Output aspect ratio. Options: match_input_image, 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3. |
| seed | number | 1 | Random seed for reproducible image edits. Leave empty for random generation. Use same seed for consistent results. |
| disable_safety_checker | boolean | false | Disable the built-in safety checker for generated images. Use with caution in production environments. |
| response_format | string | url | Format of the generated image response. Options: url (default), b64_json. |
Explore the full request and response schema in our external API documentation
Performance
Strengths & considerations
| Strengths | Considerations |
|---|---|
| Supports custom LoRA weights from HuggingFace Adjustable LoRA strength (-1.0 to 3.0 scale) Compatible with public and private HuggingFace repositories Maintains sub-second inference with LoRA applied Supports 1-5 reference images simultaneously Strong instruction and prompt adherence Turbo mode for optimized performance Reproducible results with seed parameter | Requires LoRA weights to be hosted on HuggingFace Private LoRA access requires HuggingFace API token LoRA quality depends on the training quality of the weights Maximum of 5 images per request Requires at least one input image (not text-only) LoRA loading adds slight overhead to first request |
Use cases
Recommended applications for this model
Enterprise
Platform Integration
Docker Support
Official Docker images for containerized deployments
Kubernetes Ready
Production-grade KBS manifests and Helm charts
SDK Libraries
Official SDKs for Python, Javascript, Go, and Java
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