Skip to main content
NewSeedance 2.5 is live→
ModelRunner
shallowdream204 avatar

BitDance Text to Image API

shallowdream204/bitdance

Generate fast, high-resolution, photorealistic images from text prompts using an advanced autoregressive model for efficient, high-quality results.

0.01
GitHub
License
Weights
OpenAPI

Model Input

Input

Text prompt for image generation.

The size of the generated image. Will be snapped to the nearest supported resolution.

Min: 10 - Max: 100

Number of diffusion sampling steps per decoding step. Higher values (e.g. 50) improve quality at the cost of speed.

Min: 1 - Max: 15

Classifier-free guidance scale. Higher values follow the prompt more closely.

Random seed for reproducibility. The same seed and prompt will produce the same image.

The format of the generated image.

Safety checker can only be disabled on API call

Min: 1 - Max: 4

The number of images to generate. Each generated image is billed.

You need to be logged in to run this model and view results.
Log in

Model Output

Output

Fill in the input form and click submit to see the output
Logs (1 lines)

Model Example Requests

Examples

Example output 1Example output 2Example output 3Example output 4

BitDance Text to Image API

BitDance Text to Image is a text-to-image AI model by shallowdream204. On ModelRunner it runs through a REST API or via MCP from any AI assistant, at $0.01 per image.

POST https://queue.modelrunner.run/shallowdream204/bitdance

cURL

# Submit a request to the queue. Input fields go at the top level of the
# body. The optional reserved "metadata" object holds your own flat string
# tags — stored on the request, never sent to the model; filter later with
# GET https://queue.modelrunner.run/requests?metadata=<url-encoded JSON>.
curl -X POST https://queue.modelrunner.run/shallowdream204/bitdance \
  -H "Authorization: Key $MRUN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "your prompt here",
    "metadata": {
      "project": "my-project"
    }
  }'
# → { "request_id": "...", "status_url": "...", "response_url": "..." }

# Poll status_url until "COMPLETED", then fetch the result
curl "https://queue.modelrunner.run/shallowdream204/bitdance/requests/$REQUEST_ID/status" \
  -H "Authorization: Key $MRUN_API_KEY"
curl "https://queue.modelrunner.run/shallowdream204/bitdance/requests/$REQUEST_ID" \
  -H "Authorization: Key $MRUN_API_KEY"

JavaScript

import { modelrunner } from "@modelrunner/client";

const result = await modelrunner.subscribe("shallowdream204/bitdance", {
  input: {
    "prompt": "your prompt here"
  },
});
console.log(result);

Python

import os
import requests

headers = {"Authorization": f"Key {os.environ['MRUN_API_KEY']}"}

submitted = requests.post(
    "https://queue.modelrunner.run/shallowdream204/bitdance",
    headers=headers,
    json={
      "prompt": "your prompt here"
    },
).json()

# Poll submitted["status_url"] until "COMPLETED", then:
result = requests.get(submitted["response_url"], headers=headers).json()

Input parameters

NameTypeRequiredDescription
promptstringyesText prompt for image generation.
image_sizeenumnoThe size of the generated image. Will be snapped to the nearest supported resolution. Default: "square_hd".
num_inference_stepsintegernoNumber of diffusion sampling steps per decoding step. Higher values (e.g. 50) improve quality at the cost of speed. Default: 25.
guidance_scalenumbernoClassifier-free guidance scale. Higher values follow the prompt more closely. Default: 7.5.
seedintegernoRandom seed for reproducibility. The same seed and prompt will produce the same image.
output_formatenumnoThe format of the generated image. Default: "jpeg".
enable_safety_checkerbooleannoIf set to true, the safety checker will be enabled. Default: true.
num_imagesintegernoThe number of images to generate. Each generated image is billed. Default: 1.

Machine-readable: OpenAPI schema · llms.txt

Use BitDance Text to Image from Claude & Cursor (MCP)

Point Claude Code, Claude Desktop, Cursor, or any MCP client at the ModelRunner MCP server and BitDance Text to Image becomes a tool your assistant can call directly — it authorizes via OAuth (no API key in config) and runs this model with the run_model tool using the endpoint shallowdream204/bitdance.

MCP client config (Claude Desktop, Cursor)

{
  "mcpServers": {
    "modelrunner": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://mcp.modelrunner.run/mcp"]
    }
  }
}

Claude Code

claude mcp add --transport http modelrunner https://mcp.modelrunner.run/mcp

Then ask your assistant, for example: “Run shallowdream204/bitdance on ModelRunner to generate image”. MCP setup guide.

Model Details

Model Details

BitDance is a powerful autoregressive model designed for generating high-resolution, photorealistic images from text descriptions. It leverages advanced techniques to produce fast, high-quality visuals, making it an excellent tool for artists, designers, and creators who need to bring their textual ideas to life.

The model's core capability is transforming a descriptive text prompt into a detailed image. You can guide the generation process with a high degree of control through various parameters.

### Key Controls

* **Prompt**: The primary input. The more descriptive and detailed your prompt, the more tailored the resulting image will be. Specify subjects, settings, artistic styles, lighting, and composition. * **Image Size**: Choose from a variety of aspect ratios, including square, portrait (4:3, 16:9), and landscape (4:3, 16:9), to fit your specific needs. * **Inference Steps & Guidance Scale**: Fine-tune the image generation process. `num_inference_steps` controls the trade-off between speed and quality, with higher values producing more refined images. `guidance_scale` determines how strictly the model adheres to your prompt. * **Seed**: Use a specific seed to ensure reproducible results, allowing you to generate the same image again or make subtle tweaks from a known starting point. * **Number of Images**: Generate up to four images from a single prompt to explore different variations and select the best outcome.

### Getting the Best Results

For optimal results, write clear and specific prompts. For instance, instead of "a cat," try "A close-up portrait of a fluffy calico cat wearing a tiny top hat, cinematic photography style, soft natural lighting." Experiment with the `guidance_scale` to find the right balance between prompt adherence and creative freedom. Using the `seed` parameter is highly recommended when you want to iterate on a promising result.

To run via the Javascript client, use the following code: ```javascript import { modelrunner } from "@modelrunner/client";

const result = await modelrunner.subscribe('shallowdream204/bitdance', { input: { "prompt": "A vibrant, detailed painting of a mystical forest at twilight, with glowing mushrooms and ethereal creatures, in the style of fantasy concept art", "image_size": "landscape_16_9", "num_inference_steps": 30, "guidance_scale": 8.0, "num_images": 2 } });

console.log(result); ```