API reference · Baidu

baidu/ernie-image-trainer

Integrate this model through SandBase's unified API, with production-ready schemas and examples.

IMAGEAsyncOpen model

Production endpoint

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OpenAI-compatible endpoint with unified authentication and usage tracking.

POSThttps://api.sandbase.ai/v1/run

Model IDbaidu/ernie-image-trainer

Input Schema

4 parameters · 0 required · 4 optional

Parameter	Type	Required	Description
`steps`	integer	Optional	Number of steps to train for · Min: 10 · Max: 40000 · Default: 2000
`learning_rate`	number	Optional	Learning rate. · Default: 0.0005
`default_caption`	string	Optional	Default caption to use when caption files are missing. If None, missing captions will cause an error.
`images_data_url`	string	Optional	URL to the input data zip archive. The zip should contain pairs of images and corresponding captions. The images should be named: ROOT.EXT. For example: 001.jpg The corresponding captions should be named: ROOT.txt. For example: 001.txt If no text file is provided for an image, the default_caption will be used.

Output Schema

Field	Type	Description
`id`	string	Unique identifier for the generation task
`status`	string	Task status: pending, running, completed, failed, timeout
`model`	string	Model used for the generation
`outputs`	array	Array of output items
`outputs[].url`	string	URL of the generated artifact
`outputs[].content_type`	string	MIME type (e.g. image/png, video/mp4)
`error`	object \| null	Error details if failed, null on success
`error.type`	string	Machine-readable error type code
`error.message`	string	Human-readable error description

Async Workflow

This model uses asynchronous execution. Submit a request and poll for the result.

Submit — POST to /v1/run, receive an id
Poll — GET /v1/run/{id} until status is completed, failed, or timeout
Retrieve — Read outputs from the completed response

Code Examples

Ready-to-run snippets

const apiKey = process.env.SANDBASE_API_KEY;
const response = await fetch("https://api.sandbase.ai/v1/run", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "baidu/ernie-image-trainer",
    "steps": 2000,
    "learning_rate": 0.0005
  }),
});

if (!response.ok) throw new Error(await response.text());
let result = await response.json();
for (let attempt = 0; attempt < 120 && !["completed", "failed", "timeout"].includes(result.status); attempt++) {
  await new Promise((resolve) => setTimeout(resolve, 2_000));
  const poll = await fetch(`https://api.sandbase.ai/v1/run/${result.id}`, {
    headers: { Authorization: `Bearer ${apiKey}` },
  });
  if (!poll.ok) throw new Error(await poll.text());
  result = await poll.json();
}
if (result.status !== "completed") throw new Error(`Generation ended: ${result.status}`);
console.log(result);

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