Stable Audio 3 Trainer
集成
模型 id
stable-audio-3-trainer
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/stable-audio-3-trainer?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"audio_data_url": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
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"])
# 1. Connect once (Claude Code; Cursor, VS Code, Claude Desktop: https://doitong.com/zh/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.com/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "stable-audio-3-trainer",
"input": {
"audio_data_url": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
}
}
通过 Doitong API 调用 Stable Audio 3 Trainer 模型(stable-audio-3-trainer)。智能体文档:https://doitong.com/zh/developers/models/stable-audio-3-trainer.md
POST https://api.doitong.com/v1/run/stable-audio-3-trainer?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"audio_data_url": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
}
如果响应状态为 "queued" 或 "running",请轮询 GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20,直到状态变为 "succeeded";文件位于 outputs[].url。使用相同请求体 POST https://api.doitong.com/v1/quote/stable-audio-3-trainer,可在运行前返回确切价格。
与示例类似的文件: $3.00 3,000 API 积分 运行前会测量你的文件 在此页面运行
你的新 API 密钥。 它仅在此时显示,并且已填入下方的代码和 API 密钥字段中。请妥善保密:切勿将其放入在浏览器中运行的代码。
构建请求
控件根据模型架构生成。更改控件时,代码和价格会同步更新。
POST
/run/stable-audio-3-trainer?wait=20
报价 → $3.00
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/stable-audio-3-trainer?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"audio_data_url": "https://content.doitong.com/audio/showcase/v3/tools/dub_es.mp3"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
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"])
{
"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
}
}
}
关于 Stable Audio 3 Trainer
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。
参数
名称类型
默认值允许值
描述
audio_data_url必填
类型string
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可选
类型enum
默认值medium-base
medium-basesmall-music-basesmall-sfx-base
用于微调 Stable Audio 3 的基础检查点。
number_of_steps可选
类型integer
默认值1000
1 – 20,000
LoRA 训练的步骤数。
learning_rate可选
类型number
默认值0.0001
≤ 0.01> 0
AdamW 应用于 LoRA 参数的学习率。
rank可选
类型integer
默认值16
1 – 256
LoRA 适配器的秩。
adapter_type可选
类型enum
默认值dora-rows
loradoradora-rowsdora-colsboralora-xsdora-rows-xsdora-cols-xsbora-xs
用于 LoRA 训练的适配器系列。
duration可选
类型number | null
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可选
类型integer
默认值1
1 – 8
训练期间使用的批量大小。
seed可选
类型integer
默认值42
0 – 2,147,483,647
随机化种子。
base_precision可选
类型enum
默认值bf16
bf16bfloat16fp16float16
冻结基础权重使用的精度;LoRA 参数仍保持 fp32。
include可选
类型string[]
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可选
类型string[]
用于排除匹配模块的名称子字符串。
lora_checkpoint_url可选
类型string | null
可选的 `.safetensors` LoRA 检查点 URL,用于恢复训练。
pre_encode可选
类型boolean
默认值false
在 LoRA 训练前,将音频存档预编码为 SAME 潜变量。
必填
输出
GET /requests/req_8k2m4q7x1z9c3v5b6n0p2r4t
{
"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"
}
}
你的文件,由你选择每个 outputs[].url 都是存储中的副本:可永久保存(按 GB-月付费),也可免费保存 7 天,由账户设置或 ?storage= 决定。
每个模型的结构相同图像、视频和音频均包含 type、url、content_type、width、height 和 duration。output 是模型自身的结果对象。
输出字段
- 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。
更多模型:训练
对于 AI 代理:此页面的 Markdown 版本位于 https://doitong.com/zh/developers/models/stable-audio-3-trainer.md. 所有模型和指南: https://doitong.com/developers/llms.txt