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SDXL

Embeddings are vector representations of words or phrases. In textual inversion, embeddings are used to capture the semantic meaning of the new concept or style that you want to teach the model. The model learns to associate the embedding with the example images, allowing it to generate images that are consistent with the concept or style.

To use embeddings, you will need to mention the ID of the embeddings model in model_id and you will need to include the trigger words from the embedding model in the prompt.

Tip
  • You can pass the words in the negative and/or the positive prompt based on how the model was trained.
  • Embeddings models can be used for text2image, image2image and inpainting tasks.

import requests
import json
url = "https://api.imagepipeline.io/sdxl/text2image/v1"
headers = {
"API-Key": "Your API Key"
}
data = {
"model_id": "sdxl",
"prompt": "Close up of beautiful young woman with red hair, detailed eyes、detailed face, detailed skin, standing in a field of wildflowers, wearing a flowing white dress, cinematic-2, 8k quality",
"negative_prompt": "ac_neg1, error, cropped, worst quality, low quality, duplicate, blurry, (unfinished objects), stock image, artifacts, blurry face, bad proportion, (deformed iris), too many fingers",
"num_inference_steps": 20,
"refiner": false,
"samples": 1,
"guidance_scale": 7.5,
"width": 768,
"height": 768,
"embeddings" : "15f002de-bf0c-4b99-857b-a7a4bd7030dc",
"seed": 12345,
"safety_checker": true
}
response = requests.post(url, headers=headers, data=json.dumps(data))
print(response.json())

JSON Parameters

ParameterPermissible valuesNotes
model_idstrmodel_id can be found in models page. Filter by SDXL models
promptstr, 75 tokensCheck our Prompt Guide for tips. Please add embeddings prompts to your prompt
negative_promptstr, 75 tokensCheck our Prompt Guide for tips. Please add embeddings prompts to your prompt
num_inference_stepsint, [1-100]Noise is removed with each step, resulting in a higher-quality image over time. Ideal value 20-30
strengthfloat, [0-1]Optional denoise strength
samplesint, [1-4]Generates a maximum of 4 samples per API call
guidance_scalefloat, [1-20]Higher guidance scale prioritizes text prompt relevance but sacrifices image quality. Ideal value 7.5-12.5
widthintWidth in pixels. Higher than or equal to 768 for best results
heightintHeight in pixels. Higher than or equal to 768 for best results
seedintControlling the seed can help you generate reproducible images
embeddingsstrPass the model_id of embeddings models that can be found in models page
safety_checkerbooleanChecks for NSFW images and filters explicit images

Status

Your response will include a status.

  • If the status = SUCCESS, you will also have download_urls that will have the links to your generated image based on the number of samples you have entered. The maximum number of samples that can be generated is 4.
  • If the status = PENDING, you will receive a id. You can use the status endpoint to fetch your image using the id.
  • If the status = FAILURE, you will receive only an error message.

Use the respective endpoint to fetch the status:

  • https://api.imagepipeline.io/sdxl/text2image/v1/status/{{id}}

  • https://api.imagepipeline.io/sdxl/image2image/v1/status/{{id}}

  • https://api.imagepipeline.io/sdxl/inpainting/v1/status/{{id}}

Pass the API-Key as the authorization in the header.