ReplicateImage to imageComing soon
prunaai/p-image-edit-lora
prunaai/p-image-edit-lora is an image to image tool from Replicate that runs in the background and returns images. Coming soon: listed with its price, not yet open to runs.
This tool is listed but not yet available to run.
Priced by usagePricing
$0.013 per image.
Limits
- Runs
- In the background
- Returns
- image
- Longest queue wait
- 3600s
- Run deadline
- 1800s
- Largest inline input
- 1024 KB
- Largest input file
- 500 MB
- Largest output
- 4768 MB
- Outputs per run
- 16
Input
| Field | Kind | Default | Description |
|---|---|---|---|
prompt required | text | — | Text prompt for image generation. Make sure to describe your edit task clearly. You can refer to the images as 'image 1' and 'image 2' and so on. |
lora_weights required | text | — | Load LoRA weights. Supports HuggingFace URLs in the format huggingface.co/<owner>/<model-name>[/<lora-weights-file.safetensors>]. HuggingFace LoRAs may require an API token to access, which you can provide in the `hf_api_token` input. |
seed | number (whole) | null | Random seed. Set for reproducible generation. |
turbo | true or false | true | If turned on, the model will run faster with additional optimizations. For complicated tasks, it is recommended to turn this off. |
images | list | [] | Images to use as a reference. For editing task, provide the main image as the first image. |
lora_scale | number -1 to 3 | 1 | Determines how strongly the main LoRA should be applied. |
aspect_ratio | JSON | match_input_image | Aspect ratio for the generated image. `match_input_image` will match the aspect ratio of the first image. |
hf_api_token | text | null | HuggingFace API token. If you're using a HuggingFace LoRAs that needs authentication, you'll need to provide an API token. |
Same request in code
curl https://api.spiral.ai/v1/runs \
-H "Authorization: Bearer $SPIRAL_API_KEY" \
-H "Content-Type: application/json" \
-H "Idempotency-Key: $(uuidgen)" \
-d '{
"provider": "replicate",
"model": "prunaai/p-image-edit-lora",
"input": {
"prompt": "<prompt>",
"lora_weights": "<lora_weights>"
}
}'