# MiniMax H3 Reference to Video LoRA Trainer API

> Kifundisha LoRA cha video yenye masharti ya marejeleo, chenye kuanza kwa joto kutoka LoRA ya awali

Hufundisha LoRA kwenye zip ya klipu za video za wahusika ili ingizo la marejeleo liweze kuongoza uzalishaji wa video. `reference_conditioning_p` huweka mara ngapi marejeleo yatumiwe wakati wa mafunzo, na `resume_from_lora_url` huendelea kutoka LoRA iliyofundishwa awali. Pia inaweza kusanidiwa: `rank`, `number_of_steps`, `number_of_frames`, `frame_rate` na `aspect_ratio`. Hurejesha uzani na faili la usanidi.

- Model id: `minimax/h3/ref2va/trainer`
- Made by: MiniMax
- Category: Training
- Output: file
- Price: $0.015 / step (cheapest run $30.00 (30000 API credits))
- Run: `POST https://api.doitong.com/v1/run/minimax/h3/ref2va/trainer`
- Quote: `POST https://api.doitong.com/v1/quote/minimax/h3/ref2va/trainer`
- Docs page: https://doitong.com/sw/developers/models/minimax/h3/ref2va/trainer

## Pricing

Price: **$0.015 / step**. Billed per training step (`number_of_steps`).

The full example input below costs $30.00 = 30000 API credits (2000 steps × 15 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/ref2va/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 ya ZIP ya video za mafunzo ya mhusika; seti za data za picha pekee na nyaraka mchanganyiko za mafunzo ya picha/video hukataliwa, hivyo picha lazima ziwe sidecar za marejeleo. Ziada za hiari hushiriki jina la msingi la kila klipu: manukuu kama `clip01.txt` na marejeleo yaliyopangwa kutoka `ref_1` hadi `ref_4`, yenye majina `clip01.ref_1.<ext>` hadi `clip01.ref_4.<ext>`; bila sidecar za marejeleo, fremu ya klipu hutoa rejeleo lake. `<ext>` huamua modali ya rejeleo: picha (.png/.jpg/.jpeg), sauti (.wav/.mp3/.flac/.m4a/.ogg/.aac), au video (.mp4/.mov/.avi/.mkv/.webm), ambazo nyimbo zake za sauti pia huwa marejeleo ya sauti. Klipu za mafunzo zinaunga mkono .mp4, .mov, .avi, na .mkv; lenga angalau klipu 10, huku zaidi zikفضلiwa. |
| `rank` |  | enum (integer) | no | `32` | `8`, `16`, `32`, `64`, `128` | Daraja la urekebishaji la LoRA, linalobadilisha matumizi makubwa ya kumbukumbu kwa uwezo mkubwa zaidi kadiri mpangilio unavyoongezeka. |
| `number_of_steps` |  | integer | no | `2000` | 1 – 15,000 | Jumla ya idadi ya hatua za mafunzo. |
| `learning_rate` |  | number | no | `0.0002` | 0.000001 – 1 | Kiwango cha kujifunza cha uboreshaji, kinachosawazisha ongezeko linalowezekana la kasi ya mafunzo dhidi ya hatari ya overfitting kinapoongezwa. |
| `number_of_frames` |  | integer | no | `73` | 22 – 124 | Idadi ya fremu kwa kila sampuli ya mafunzo; kuigawa kwa 17 lazima kuache salio la 5. Mifano ni 22, 39, 56, 73, 90, 107, na 124. |
| `frame_rate` |  | integer | no | `24` | 8 – 60 | Kasi lengwa ya fremu ya video, inayopimwa kwa fremu kwa sekunde. |
| `resolution` |  | enum (string) | no | `medium` | `low`, `medium`, `high` | Mwonekano wa mafunzo. Kuongeza mwonekano huongeza mahitaji ya kumbukumbu. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `21:9`, `16:9`, `4:3`, `1:1`, `3:4`, `9:16` | Chagua uwiano wa pande wa mafunzo kutoka seti ileile inayopatikana kupitia MiniMax H3 API. |
| `trigger_phrase` |  | string | no | `` |  | Kauli ya uanzishaji wa mtindo wa LoRA, inayowekwa mwanzoni mwa manukuu wakati wa mafunzo. |
| `reference_conditioning_p` |  | number | no | `0.9` | 0 – 1 | Weka mara ngapi mafunzo yatatumia conditioning ya picha za marejeleo dhidi ya mafunzo ya text-to-video-audio yasiyo na conditioning. Uwezekano wowote uliobaki huenda kwenye lengo lisilo na conditioning ili kudumisha uzalishaji thabiti wa kutumia kidokezo pekee. |
| `resume_from_lora_url` |  | string \| null | no |  |  | URL ya mafunzo ya warm-start yenye LoRA ya .safetensors iliyoundwa awali na trainer huyu, ikifuatiwa na hatua za ziada za mafunzo za number_of_steps. Hakuna kitu isipokuwa uzani wa adapta kinachorejeshwa: uboreshaji na upangaji wa learning-rate huanza upya. |
| `auto_scale_input` |  | boolean | no | `false` |  | Iwapo fps lengwa na idadi ya fremu zitalinganishwa kupitia kuongeza ukubwa wa video kiotomatiki; true huwezesha marekebisho haya. |
| `split_input_into_scenes` |  | boolean | no | `true` |  | Washa mgawanyo wa mandhari kwa video ndefu kuliko kikomo cha muda, ukitupa sidecar za marejeleo kutoka klipu zozote zinazogawanywa. |
| `split_input_duration_threshold` |  | number | no | `30` | 1 – 60 | Kichocheo cha kugawa mandhari kinachoonyeshwa kama muda kwa sekunde: video ndefu kuliko kizingiti pekee ndizo hugawanywa. |
| `debug_dataset` |  | boolean | no | `false` |  | Chaguo la kupakua jalada kwa kukagua uchakataji wa awali kabla ya kuanzisha mafunzo kamili. Ikiwezeshwa, trainer huweka seti ya data iliyochakatwa kwenye jalada ili uweze kukagua mwenyewe manukuu, picha za marejeleo, video na picha kwa usahihi. |
| `strict_dataset` |  | boolean | no | `false` |  | Ushughulikiaji mkali wa matatizo ya uchakataji wa awali ambayo vinginevyo yangeandikwa kwenye logi na kutatuliwa kwa fallback iliyoandikwa. Kuiwezesha hukataa manukuu yanayohitaji vidokezo tupu, sidecar za marejeleo zinazokosekana, na video zenye sauti isiyosomeka badala ya kuruhusu fallback hizo. |

## 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/ref2va/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/ref2va/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/ref2va/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/ref2va/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/ref2va/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": 30000,
    "usd": "30.00",
    "charged": 30000,
    "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 ya uzito wa LoRA uliofunzwa katika umbizo la .safetensors. |
| `config_file` | object {url, content_type, file_name, file_size} | Usanidi wa kuweka endpoint ya uelekezaji. |
| `debug_dataset` | object {url, content_type, file_name, file_size} \| null | Inapatikana tu kwa maombi yenye `debug_dataset` iliyowezeshwa; jalada hili linaloweza kupakuliwa huhifadhi data ya mafunzo baada ya uchakataji wa awali. |

## 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 Image to Video Audio LoRA Trainer](https://doitong.com/developers/models/minimax/h3/i2v/trainer.md) (`minimax/h3/i2v/trainer`): $0.01 / 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/ref2va/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/ref2va/trainer
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/minimax/h3/ref2va/trainer