lykon/dreamshaper-8-lcm

Updated on Jun 11, 2025 Published on Mar 14, 2025

A Stable Diffusion model refined for improved photorealism while maintaining a broad range of capabilities.

Model Name lykon/dreamshaper-8-lcm
Model Type Image Generation
Model Cost $0.006 Per Image
Model Hosted (Region) US
Model Available (Region) Global
Model Base Architecture Diffusion
Model Endpoint Access URL https://cloud.dataoorts.com/api/v1

Get Your API Credential From: https://cloud.dataoorts.com/ai

import requests
import json

## Define the endpoint URL
url = 'https://cloud.dataoorts.com/api/v1'

## Define the headers including the API Authorization token
headers = {
    'Content-Type': 'application/json',
    'Authorization': 'Bearer $Dataoorts_Serverless_API_KEY'
}

## Define the Model Name and Data Payload with Optional Additional Hyper-Parameters
payload = {
    "model": "lykon/dreamshaper-8-lcm",
    "data": {
        ## Required: A text description of the image you want to generate (min 2)
        "prompt": "futuristic spacecraft",
        ## Optional: Text describing elements to avoid in the generated image
        #"negative_prompt": "blurry, low quality, deformed",
        ## Optional: Height of the generated image in pixels (min 256, max 2048)
        #"height": 512,
        ## Optional*: Width of the generated image in pixels (min 256, max 2048)
        #"width": 512,
        ## Optional: Number of diffusion steps; default is 20 (max 20)
        #"num_steps": 20,
        ## Optional: Guidance scale; higher values make the image more aligned with the prompt (default 7.5)
        #"guidance": 7.5
    }
}

## Make the POST request and save the output to a file
response = requests.post(url, headers=headers, data=json.dumps(payload))
## Save the response content as an image file
with open('output.png', 'wb') as f:
    f.write(response.content)
print("Image saved as output.png")

The provided example for API access is written in Python, but you can use any programming language of your choice to adapt and transform the code as needed. Below, the example output image is shared for reference.

output.png