# Stable Audio 3 Trainer API

> 根据带有匹配文本说明的音频片段 zip，为 Stable Audio 3 训练 LoRA

在 `audio_data_url` 指向的 zip 上微调基础检查点（medium-base、small-music-base 或 small-sfx-base）；其中每个音频文件都必须有同名的 `.txt` 说明文件。可调整 `number_of_steps`（最多 20000）、`learning_rate`、`rank`（1 到 256）、`adapter_type` 和 `batch_size`，也可以从 `.safetensors` 检查点继续训练。返回 LoRA 权重和配置文件。

- Model id: `stable-audio-3-trainer`
- Made by: Stability AI
- Category: Training
- Output: file
- Price per run: from $0.003 / run (cheapest run $0.003 (3 API credits))
- Run: `POST https://api.doitong.com/v1/run/stable-audio-3-trainer`
- Quote: `POST https://api.doitong.com/v1/quote/stable-audio-3-trainer`
- Docs page: https://doitong.com/zh/developers/models/stable-audio-3-trainer

## Pricing

Price: **from $0.003 / run** (the lowest tier; the quote prices your exact input). Price per run: the input files are measured before the run (length, resolution, frame rate). The quote measures the same files and is exactly what the run charges.

The full example input below costs $3.00 = 3000 API credits (1 run × $3.00).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.com/v1/quote/stable-audio-3-trainer` with the same JSON body returns the exact price for that input; the quote is exactly what a run charges. Invalid input is never charged and failed or canceled requests are refunded automatically.

## Input parameters

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `audio_data_url` |  | string | yes |  |  | 数据集 zip URL，每个音频/字幕对以匹配的基本文件名共同存储：例如 `clip.wav` 与 `clip.txt` 配对。字幕必须使用 `.txt` 扩展名。 |
| `model` |  | enum (string) | no | `medium-base` | `medium-base`, `small-music-base`, `small-sfx-base` | 用于微调 Stable Audio 3 的基础检查点。 |
| `number_of_steps` |  | integer | no | `1000` | 1 – 20,000 | LoRA 训练的步骤数。 |
| `learning_rate` |  | number | no | `0.0001` | ≤ 0.01, > 0 | AdamW 应用于 LoRA 参数的学习率。 |
| `rank` |  | integer | no | `16` | 1 – 256 | LoRA 适配器的秩。 |
| `adapter_type` |  | enum (string) | no | `dora-rows` | `lora`, `dora`, `dora-rows`, `dora-cols`, `bora`, `lora-xs`, `dora-rows-xs`, `dora-cols-xs`, `bora-xs` | 用于 LoRA 训练的适配器系列。 |
| `duration` |  | number \| null | no |  | 1 – 380 | 裁剪/填充时长，以秒计；任何情况下都受所选模型原生训练长度限制。提供长度，或省略该值以使用数据集中检测到的最长片段，但不能超过该上限。 |
| `batch_size` |  | integer | no | `1` | 1 – 8 | 训练期间使用的批量大小。 |
| `seed` |  | integer | no | `42` | 0 – 2,147,483,647 | 随机化种子。 |
| `base_precision` |  | enum (string) | no | `bf16` | `bf16`, `bfloat16`, `fp16`, `float16` | 冻结基础权重使用的精度；LoRA 参数仍保持 fp32。 |
| `include` |  | array of string \| null | no |  |  | 限制 LoRA 添加位置的模块名称子字符串：只有匹配的模块会接收 LoRA。 |
| `exclude` |  | array of string \| null | no |  |  | 用于排除匹配模块的名称子字符串。 |
| `lora_checkpoint_url` |  | string \| null | no |  |  | 可选的 `.safetensors` LoRA 检查点 URL，用于恢复训练。 |
| `pre_encode` |  | boolean | no | `false` |  | 在 LoRA 训练前，将音频存档预编码为 SAME 潜变量。 |

## Example input

Required parameters only:

```json
{
  "audio_data_url": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
}
```

A fuller example:

```json
{
  "audio_data_url": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
}
```

## Run it

Set `DOITONG_API_KEY` to a key from https://doitong.com/developers/dashboard#keys. `?wait=20` returns the finished request in the same call when it is ready within 20 seconds; otherwise poll `GET /requests/{id}` (it also accepts `?wait=`), or pass `webhook_url`.

### curl

```bash
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/stable-audio-3-trainer?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "audio_data_url": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
  }'

# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.com/v1";
const headers = {
  "Authorization": "Bearer " + process.env.DOITONG_API_KEY,
  "Content-Type": "application/json",
};

// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/stable-audio-3-trainer?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "audio_data_url": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
  }),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);

// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
  res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
  request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
```

### Python

```python
import os
import requests

API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "audio_data_url": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/stable-audio-3-trainer", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
    raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])

# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
    request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
    raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
```

### MCP

The MCP server at `https://api.doitong.com/v1/mcp` exposes the tools `search_models`, `get_model`, `quote`, `run`, `get_request`, `cancel_request`, `list_requests`, `create_upload` and `get_account`. A `run` call for this model:

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "run",
    "arguments": {
      "model_id": "stable-audio-3-trainer",
      "input": {
        "audio_data_url": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
      },
      "wait_seconds": 20
    }
  }
}
```

## Response

Every call returns a request object. `status` is one of `queued`, `running`, `succeeded`, `failed`, `canceled`. `outputs` lists the generated files with URLs on our storage (kept forever, or 7 days with `?storage=temporary`; `storage` says which); `output` is the model's own result object with the same URLs.

```json
{
  "id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
  "object": "request",
  "model": "stable-audio-3-trainer",
  "status": "succeeded",
  "created_at": "2026-10-20T12:00:00Z",
  "started_at": "2026-10-20T12:00:02Z",
  "completed_at": "2026-10-20T12:00:09Z",
  "queue_position": null,
  "cost": {
    "credits": 3000,
    "usd": "3.00",
    "charged": 3000,
    "refunded": 0
  },
  "input": {
    "audio_data_url": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
  },
  "output": {
    "lora_file": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    },
    "config_file": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    }
  },
  "outputs": [
    {
      "type": "file",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "stored": true
    }
  ],
  "error": null,
  "metrics": {
    "inference_seconds": 6.8
  },
  "urls": {
    "self": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `lora_file` | object {url, content_type, file_name, file_size} | 为 Stable Audio 3 训练的 LoRA 权重。 |
| `config_file` | object {url, content_type, file_name, file_size} | 描述训练运行及兼容推理模型的 JSON 元数据。 |

## Related models

- [ERNIE-Image Trainer](https://doitong.com/developers/models/ernie-image-trainer.md) (`ernie-image-trainer`): $0.0012 / step
- [FLUX 2 \[klein\] 9b Base Trainer](https://doitong.com/developers/models/flux-2-klein-9b-base-trainer.md) (`flux-2-klein-9b-base-trainer`): $0.0043 / step
- [Flux 2 Klein 9B Base Trainer](https://doitong.com/developers/models/flux-2-klein-9b-base-trainer/edit.md) (`flux-2-klein-9b-base-trainer/edit`): $0.0139 / step
- [FLUX 2 Trainer](https://doitong.com/developers/models/flux-2-trainer.md) (`flux-2-trainer`): $0.0064 / step
- [FLUX 2 Trainer Edit](https://doitong.com/developers/models/flux-2-trainer/edit.md) (`flux-2-trainer/edit`): $0.0389 / step
- [FLUX 2 Trainer V2](https://doitong.com/developers/models/flux-2-trainer-v2.md) (`flux-2-trainer-v2`): $0.0064 / step
- [FLUX 2 Trainer V2 Edit](https://doitong.com/developers/models/flux-2-trainer-v2/edit.md) (`flux-2-trainer-v2/edit`): $0.0389 / step
- [Flux Kontext Trainer](https://doitong.com/developers/models/flux-kontext-trainer.md) (`flux-kontext-trainer`): from $1.25 / run

## Links

- HTML page: https://doitong.com/developers/models/stable-audio-3-trainer
- All models and guides for AI agents: https://doitong.com/developers/llms.txt
- OpenAPI 3.1 with this model's typed request body: https://doitong.com/developers/openapi.json?model=stable-audio-3-trainer
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/stable-audio-3-trainer