# MiniMax H3 Image to Video Audio LoRA Trainer API

> Pelatih LoRA yang mengajar image-ke-video bingkai pertama dengan audio daripada klip video

Melatih LoRA daripada zip klip video dalam `training_data_url`, menggunakan pengkondisian bingkai pertama supaya imej pegun boleh dihidupkan menjadi video. Dataset mestilah mengandungi video sahaja. Tetapan termasuk `rank` 8 hingga 128, `number_of_steps` sehingga 15000, `number_of_frames` daripada 22 hingga 124, `frame_rate` daripada 8 hingga 60 dan `trigger_phrase`. Menghasilkan berat LoRA dan fail konfigurasi.

- Model id: `minimax/h3/i2v/trainer`
- Made by: MiniMax
- Category: Training
- Output: file
- Price: $0.01 / step (cheapest run $20.00 (20000 API credits))
- Run: `POST https://api.doitong.com/v1/run/minimax/h3/i2v/trainer`
- Quote: `POST https://api.doitong.com/v1/quote/minimax/h3/i2v/trainer`
- Docs page: https://doitong.com/ms/developers/models/minimax/h3/i2v/trainer

## Pricing

Price: **$0.01 / step**. Billed per training step (`number_of_steps`).

The full example input below costs $20.00 = 20000 API credits (2000 steps × 10 API credits).

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/minimax/h3/i2v/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 |
|---|---|---|---|---|---|---|
| `training_data_url` |  | string | yes |  |  | URL ZIP yang mengandungi video latihan dalam format .mp4, .mov, .avi atau .mkv; sekurang-kurangnya 10 klip disyorkan, dan koleksi yang lebih besar adalah lebih baik. Imej tidak boleh menjadi media latihan: set data imej sahaja dan arkib yang mencampurkan imej latihan dengan video akan ditolak, walaupun sesetengah endpoint membenarkan imej sebagai sidecar pelaziman. Fail kapsyen pilihan boleh disertakan bersama klip, dengan setiap fail teks berkongsi nama asas videonya. |
| `rank` |  | enum (integer) | no | `32` | `8`, `16`, `32`, `64`, `128` | Rank penyesuaian LoRA, menukar penggunaan memori yang meningkat dengan kapasiti yang lebih besar apabila tetapan dinaikkan. |
| `number_of_steps` |  | integer | no | `2000` | 1 – 15,000 | Jumlah langkah latihan. |
| `learning_rate` |  | number | no | `0.0002` | 0.000001 – 1 | Kadar pembelajaran pengoptimuman, mengimbangi kemungkinan peningkatan kelajuan latihan dengan risiko terlebih suai apabila dinaikkan. |
| `number_of_frames` |  | integer | no | `73` | 22 – 124 | Bilangan bingkai bagi setiap sampel latihan; pembahagiannya dengan 17 mesti meninggalkan baki 5. Contohnya termasuk 22, 39, 56, 73, 90, 107 dan 124. |
| `frame_rate` |  | integer | no | `24` | 8 – 60 | Kadar bingkai video sasaran, diukur dalam bingkai sesaat. |
| `resolution` |  | enum (string) | no | `medium` | `low`, `medium`, `high` | Resolusi latihan. Meningkatkan resolusi meningkatkan keperluan memori. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `21:9`, `16:9`, `4:3`, `1:1`, `3:4`, `9:16` | Pilih nisbah aspek latihan daripada set yang sama yang tersedia melalui MiniMax H3 API. |
| `trigger_phrase` |  | string | no | `` |  | Frasa pengaktifan gaya LoRA, disisipkan pada permulaan kapsyen semasa latihan. |
| `first_frame_conditioning_p` |  | number | no | `0.5` | 0 – 1 | Tingkatkan prestasi image-to-video dengan meningkatkan kekerapan latihan menggunakan pengkondisian bingkai pertama; nilai ini menetapkan kebarangkalian tersebut. |
| `auto_scale_input` |  | boolean | no | `false` |  | Sama ada fps sasaran dan bilangan bingkai dipadankan melalui penskalaan video automatik; true mendayakan pelarasan ini. |
| `split_input_into_scenes` |  | boolean | no | `true` |  | Pemisahan adegan untuk video yang melebihi ambang tempoh, didayakan apabila true. |
| `split_input_duration_threshold` |  | number | no | `30` | 1 – 60 | Pencetus pemisahan adegan yang dinyatakan sebagai tempoh dalam saat: hanya video yang lebih panjang daripada ambang akan dipisahkan. |
| `debug_dataset` |  | boolean | no | `false` |  | Mod pemeriksaan prapemprosesan untuk menyemak video, imej dan kapsyen sebelum larian latihan penuh. Mendayakannya menyebabkan pelatih mengembalikan set data latihan yang diproses dalam arkib boleh dimuat turun untuk semakan manual. |
| `strict_dataset` |  | boolean | no | `false` |  | Pengendalian ketat masalah prapemprosesan yang sebaliknya akan dilog dan diselesaikan menggunakan sandaran yang didokumenkan. Mendayakannya menolak kapsyen yang memerlukan prompt kosong, bingkai utama sidecar yang hilang dan video dengan audio tidak boleh dibaca, bukannya menggantikannya dengan prompt kosong, bingkai klip atau senyap. |

## Example input

Required parameters only:

```json
{
  "training_data_url": "https://example.com/your-file.zip"
}
```

A fuller example:

```json
{
  "training_data_url": "https://example.com/your-file.zip"
}
```

## 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/minimax/h3/i2v/trainer?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "training_data_url": "https://example.com/your-file.zip"
  }'

# 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/minimax/h3/i2v/trainer?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "training_data_url": "https://example.com/your-file.zip"
  }),
});
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 = {
    "training_data_url": "https://example.com/your-file.zip",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/minimax/h3/i2v/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": "minimax/h3/i2v/trainer",
      "input": {
        "training_data_url": "https://example.com/your-file.zip"
      },
      "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": "minimax/h3/i2v/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": 20000,
    "usd": "20.00",
    "charged": 20000,
    "refunded": 0
  },
  "input": {
    "training_data_url": "https://example.com/your-file.zip"
  },
  "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
    },
    "debug_dataset": {
      "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} | URL untuk pemberat LoRA terlatih dalam format .safetensors. |
| `config_file` | object {url, content_type, file_name, file_size} | Konfigurasi untuk persediaan endpoint inferens. |
| `debug_dataset` | object {url, content_type, file_name, file_size} \| null | Hanya tersedia untuk permintaan dengan `debug_dataset` didayakan, arkib boleh dimuat turun ini mengandungi data latihan selepas prapemprosesan. |

## Related models

- [MiniMax H3 First Last Frame LoRA Trainer](https://doitong.com/developers/models/minimax/h3/flf2v/trainer.md) (`minimax/h3/flf2v/trainer`): $0.01 / step
- [MiniMax H3 Reference to Video LoRA Trainer](https://doitong.com/developers/models/minimax/h3/ref2va/trainer.md) (`minimax/h3/ref2va/trainer`): $0.015 / step
- [MiniMax H3 Text to Video LoRA Trainer](https://doitong.com/developers/models/minimax/h3/t2v/trainer.md) (`minimax/h3/t2v/trainer`): $0.005 / step
- [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

## Links

- HTML page: https://doitong.com/developers/models/minimax/h3/i2v/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=minimax/h3/i2v/trainer
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/minimax/h3/i2v/trainer