# Stable Audio 3 Trainer API

> Traint een LoRA op Stable Audio 3 vanuit een zipbestand met audioclips en bijbehorende tekstbijschriften

Fine-tunet een basischeckpoint (medium-base, small-music-base of small-sfx-base) op een `audio_data_url`-zipbestand waarin elk audiobestand een bijschrift met dezelfde naam en de extensie `.txt` heeft. U kunt `number_of_steps` (tot 20000), `learning_rate`, `rank` (1 tot 256), `adapter_type` en `batch_size` instellen, of doorgaan vanaf een `.safetensors`-checkpoint. Retourneert LoRA-gewichten en een configuratiebestand.

- 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.ru/v1/run/stable-audio-3-trainer`
- Quote: `POST https://api.doitong.ru/v1/quote/stable-audio-3-trainer`
- Docs page: https://doitong.com/nl/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.ru/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 |  |  | URL van een dataset-zipbestand, waarbij elk audio/bijschrift-paar samen is opgeslagen met overeenkomstige basisnamen: `clip.wav` hoort bijvoorbeeld bij `clip.txt`. Bijschriften moeten de extensie `.txt` gebruiken. |
| `model` |  | enum (string) | no | `medium-base` | `medium-base`, `small-music-base`, `small-sfx-base` | Basis-checkpoint voor het finetunen van Stable Audio 3. |
| `number_of_steps` |  | integer | no | `1000` | 1 – 20,000 | Aantal stappen voor LoRA-training. |
| `learning_rate` |  | number | no | `0.0001` | ≤ 0.01, > 0 | Leersnelheid die AdamW toepast op LoRA-parameters. |
| `rank` |  | integer | no | `16` | 1 – 256 | Rank van de LoRA-adapter. |
| `adapter_type` |  | enum (string) | no | `dora-rows` | `lora`, `dora`, `dora-rows`, `dora-cols`, `bora`, `lora-xs`, `dora-rows-xs`, `dora-cols-xs`, `bora-xs` | Adapterfamilie die voor LoRA-training wordt gebruikt. |
| `duration` |  | number \| null | no |  | 1 – 380 | Duur voor croppen/padding in seconden, in alle gevallen beperkt door de native trainingslengte van het geselecteerde model. Geef een lengte op of laat deze weg om de langste in de dataset gevonden clip te gebruiken, binnen die limiet. |
| `batch_size` |  | integer | no | `1` | 1 – 8 | Batchgrootte die tijdens de training wordt gebruikt. |
| `seed` |  | integer | no | `42` | 0 – 2,147,483,647 | Seed voor randomisatie. |
| `base_precision` |  | enum (string) | no | `bf16` | `bf16`, `bfloat16`, `fp16`, `float16` | Precisie die voor de bevroren basisgewichten wordt gebruikt; LoRA-parameters blijven fp32. |
| `include` |  | array of string \| null | no |  |  | Substrings van modulenaam die bepalen waar LoRA wordt toegevoegd: alleen overeenkomende modules ontvangen deze. |
| `exclude` |  | array of string \| null | no |  |  | Naam-substrings die worden gebruikt om overeenkomende modules uit te sluiten. |
| `lora_checkpoint_url` |  | string \| null | no |  |  | Optionele URL van een `.safetensors`-LoRA-checkpoint om de training te hervatten. |
| `pre_encode` |  | boolean | no | `false` |  | Vooraf coderen van het audio-archief naar SAME-latenten vóór de LoRA-training. |

## 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.ru/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.ru/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.ru/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.ru/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.ru/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.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `lora_file` | object {url, content_type, file_name, file_size} | LoRA-gewichten die zijn getraind voor Stable Audio 3. |
| `config_file` | object {url, content_type, file_name, file_size} | JSON-metadata die de trainingsrun en het compatibele model voor inferentie beschrijft. |

## 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.ru/v1/models/stable-audio-3-trainer
