Stable Audio 3 Trainer
整合
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-TW/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"
}
}
透過 Doitong API 呼叫 Stable Audio 3 Trainer 模型(stable-audio-3-trainer)。代理程式文件:https://doitong.com/zh-TW/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"
}
如果回應狀態為 "queued" 或 "running",請輪詢 GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20,直到狀態變為 "succeeded";檔案位於 outputs[].url。使用相同主體傳送 POST https://api.doitong.com/v1/quote/stable-audio-3-trainer,可在執行前取得確切價格。
像範例一樣的檔案: $3.00 3,000 API 點數 您的檔案會在執行前計量 在此頁面執行
您的新 API 金鑰。 僅會在此時顯示,且已填入下方的程式碼與 API 金鑰欄位。請妥善保密:切勿將其放入在瀏覽器中執行的程式碼。
建立請求
控制項是根據模型結構描述生成的。變更設定時,程式碼和價格會同步更新。
POST
/run/stable-audio-3-trainer?wait=20
報價 → $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
}
}
}
關於 Stable Audio 3 Trainer
在 `audio_data_url` zip 中的基礎檢查點(medium-base、small-music-base 或 small-sfx-base)上進行微調,其中每個音訊檔案都必須有同名的 `.txt` 說明文字。可調整 `number_of_steps`(最多 20000)、`learning_rate`、`rank`(1 到 256)、`adapter_type` 和 `batch_size`,或從 `.safetensors` 檢查點繼續訓練。回傳 LoRA 權重和設定檔。
參數
名稱類型
預設值允許值
說明
audio_data_url必填
類型string
資料集 zip URL,每組音訊/字幕會以相符的基本檔名共同儲存:例如 `clip.wav` 對應 `clip.txt`。字幕必須使用 `.txt` 副檔名。
model選填
類型enum
預設值medium-base
medium-basesmall-music-basesmall-sfx-base
用於微調 Stable Audio 3 的基礎 checkpoint。
number_of_steps選填
類型integer
預設值1000
1 – 20,000
LoRA 訓練的步驟數。
learning_rate選填
類型number
預設值0.0001
≤ 0.01> 0
AdamW 套用於 LoRA 參數的學習率。
rank選填
類型integer
預設值16
1 – 256
LoRA adapter 的 rank。
adapter_type選填
類型enum
預設值dora-rows
loradoradora-rowsdora-colsboralora-xsdora-rows-xsdora-cols-xsbora-xs
用於 LoRA 訓練的 adapter 系列。
duration選填
類型number | null
1 – 380
裁切/填補長度,以秒計算,且在所有情況下都受選定模型原生訓練長度限制。提供長度,或省略以使用資料集中偵測到的最長片段,但不得超過該上限。
batch_size選填
類型integer
預設值1
1 – 8
訓練期間使用的批次大小。
seed選填
類型integer
預設值42
0 – 2,147,483,647
用於隨機化的種子。
base_precision選填
類型enum
預設值bf16
bf16bfloat16fp16float16
凍結基礎權重使用的精度;LoRA 參數維持 fp32。
include選填
類型string[]
限制 LoRA 新增位置的模組名稱子字串:只有相符的模組會套用 LoRA。
exclude選填
類型string[]
用於排除相符模組的名稱子字串。
lora_checkpoint_url選填
類型string | null
可選的 `.safetensors` LoRA checkpoint URL,用於繼續訓練。
pre_encode選填
類型boolean
預設值false
在 LoRA 訓練前,將音訊封存檔預先編碼為 SAME latents。
必填
輸出
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"
}
}
您的檔案,由您選擇每個 outputs[].url 都是儲存空間中的副本:可永久保留(按 GB-月計費),或免費保留 7 天;可透過帳戶設定或 ?storage= 設定。
所有模型使用相同結構圖片、影片和音訊皆包含 type、url、content_type、width、height 和 duration。output 是模型自己的結果物件。
輸出欄位
- lora_file
- object {url, content_type, file_name, file_size}為 Stable Audio 3 訓練的 LoRA 權重。
- config_file
- object {url, content_type, file_name, file_size}描述訓練工作及相容推論模型的 JSON 中繼資料。
更多模型:訓練
給 AI 代理程式:此頁面的 Markdown 位於 https://doitong.com/zh-TW/developers/models/stable-audio-3-trainer.md. 所有模型與指南: https://doitong.com/developers/llms.txt