dreamshaper-8-lcm

Text-to-Image • lykon • Hosted

Stable Diffusion model that has been fine-tuned to be better at photorealism without sacrificing range.

Model Info
More information	link ↗

Usage

TypeScript
curl

export interface Env {
  AI: Ai;
}

export default {
  async fetch(request, env): Promise<Response> {

    const inputs = {
      prompt: "cyberpunk cat",
    };

    const response = await env.AI.run(
      "@cf/lykon/dreamshaper-8-lcm",
      inputs
    );

    return new Response(response, {
      headers: {
        "content-type": "image/jpg",
      },
    });
  },
} satisfies ExportedHandler<Env>;

curl https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/ai/run/@cf/lykon/dreamshaper-8-lcm  \
  -X POST  \
  -H "Authorization: Bearer $CLOUDFLARE_API_TOKEN"  \
  -d '{ "prompt": "cyberpunk cat" }'

Parameters

Input
Output

prompt

stringrequiredminLength: 1A text description of the image you want to generate

negative_prompt

stringText describing elements to avoid in the generated image

height

integerminimum: 256maximum: 2048The height of the generated image in pixels

width

integerminimum: 256maximum: 2048The width of the generated image in pixels

▶image[]

arrayFor use with img2img tasks. An array of integers that represent the image data constrained to 8-bit unsigned integer values

image_b64

stringFor use with img2img tasks. A base64-encoded string of the input image

▶mask[]

arrayAn array representing An array of integers that represent mask image data for inpainting constrained to 8-bit unsigned integer values

num_steps

integerdefault: 20maximum: 20The number of diffusion steps; higher values can improve quality but take longer

strength

numberdefault: 1A value between 0 and 1 indicating how strongly to apply the transformation during img2img tasks; lower values make the output closer to the input image

guidance

numberdefault: 7.5Controls how closely the generated image should adhere to the prompt; higher values make the image more aligned with the prompt

seed

integerRandom seed for reproducibility of the image generation

The binding returns a ReadableStream with the output (check the model's output schema).

API Schemas (Raw)

Input

Output