# Wan-2.2 Text-to-Video A14B with LoRAs API

> A14B ᡤᡳᠰᡠᡵᡝᠮᡝ ᡩᡝᠣ, LoRA ᡳ ᠠᠮᠪᠠᠨ ᠪᡝ ᠠᠪᠠᠮᡝ ᠠᡳ ᠵᡠᠯᡤᡝ ᠠᠮᠠᠯᠠ ᠪᡝ ᠵᠠᠯᡳᠨᠠᠮᡝ

ᡳᠨᡝᠩᡤᡳ ᡩᡝᠣ ᠪᡝ ᠵᠠᠯᡳᠨ ᡤᡳᠰᡠᡵᡝᠨ `prompt` ᡳ ᠠᡩᠠᠯᡳ ᠪᡠᠰᡳᠮᡝ, `loras` ᡳ ᠵᠠᠯᡳᠨ ᠪᡝ ᠠᠪᠠᠮᡝ. `reverse_video` ᡩᡝᠣ ᠪᡝ ᠠᠮᠠᠯᠠ ᠵᠠᠯᡳᠨᠠᠮᡝ. `num_frames` 17 ᡩᡝᠵᡳ 161 ᡩᡝ, `resolution` 480p, 580p ᠠᡳ 720p, ᠵᡠᠩᡤᡝ 16:9, 9:16 ᠠᡳ 1:1 ᠣᠴᡳᠮᡝ. Film ᠠᡳ rife ᠵᡠᠶᡝ ᠪᡝ ᠵᠠᠯᡳᠨᠠᠮᡝ ᠠᡳ ᠵᡠᠯᡤᡝ ᠵᠠᠯᡳᠨ ᠣᠮᠪᡳ.

- Model id: `wan/v2.2-a14b/text-to-video/lora`
- Made by: Alibaba
- Category: Text to Video
- Output: video
- Estimated price per run: from $0.507 / run (cheapest run $0.507 (507 API credits))
- Run: `POST https://api.doitong.ru/v1/run/wan/v2.2-a14b/text-to-video/lora`
- Quote: `POST https://api.doitong.ru/v1/quote/wan/v2.2-a14b/text-to-video/lora`
- Docs page: https://doitong.com/mnc/developers/models/wan/v2.2-a14b/text-to-video/lora

## Pricing

Price: **from $0.507 / run** (the lowest tier; the quote prices your exact input). Estimated from the typical cost of one run. The quote is exactly what the run charges.

Price rules (the first rule that matches the input wins; a parameter you leave out counts as its default):

- When `num_frames` > 81 and `resolution` = 480p: base price × 2
- When `num_frames` > 81 and `resolution` = 580p: base price × 2
- When `num_frames` > 81 and `resolution` = 720p: base price × 2

The full example input below costs $0.507 = 507 API credits (1 request × 507 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.ru/v1/quote/wan/v2.2-a14b/text-to-video/lora` 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 |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  |  | ᠰᡠᠨᡤᠠ ᠪᡠᠶᡝᠮᡝ ᡳ ᠵᠠᠯᠠᠨ ᡳ ᡥᡡᠯᠠᠨ᠉ |
| `negative_prompt` |  | string | no | `` |  | ᠰᡠᠨᡤᠠ ᠪᡠᠶᡝᠮᡝ ᡩᡝ ᠵᠠᠯᠠᠮᡝ ᠮᡠᠰᡝ ᡥᡡᠯᠠᠨ᠉ |
| `num_frames` |  | integer | no | `81` | 17 – 161 | ᠪᡠᠶᡝᠮᡝ ᡳ ᡶᡳᠯᡝᠮᡝ ᡳᠨᡠᠮᠪᡳ᠂ 17–161 ᡩᡝ ᠪᠠᡳᠴᡳᠨᠠᠮᠪᡳ᠉ |
| `frames_per_second` |  | integer \| null | no | `16` | 4 – 60 | ᠪᡠᠶᡝᠮᡝ ᠰᡠᠨᡤᠠ ᡳ ᡶᡳᠯᡝᠮᡝ ᡳ ᠵᠠᠰᡳᠨ 4 ᡩᡝᠴᡳ 60 ᡩᡝ᠂ `adjust_fps_for_interpolation` ᠪᡝ false ᠪᡠᠮᡝᠨ ᠰᡠᠮᡝᠮᠪᡳ᠉ ᠵᠠᠨ ᡳ ᠵᠠᠰᡳᠨ true ᠪᠠ 1 ᡳ ᠵᠠᠰᡳᠮᡝᠨ ᡩᡝ ᠰᡝᠨᡩᡝᠮᡝᠨ 16 FPS ᡩᡝ 32 FPS ᠪᠠᠶᠠᠨ᠉ |
| `seed` |  | integer \| null | no |  |  | ᠪᡠᠶᡝᠮᡝ ᡩᡝ ᠰᠠᡳᠨ ᠪᡳᠰᡳᠮᡝ ᠪᠠᠨᠵᡳᠨᠠᠮᡝ᠉ None ᡩᡝ ᠪᡳᠮᡝ ᠪᠠᠨᠵᡳᠨ ᡤᠣᠯᠣᠮᡝ᠉ |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `580p`, `720p` | ᠪᡠᠶᡝᠮᡝ ᠰᡠᠨᡤᠠ ᡳ ᠵᠠᠯᠠᠨ᠄ 480p᠂ 580p ᠠᡴᡳ 720p᠉ |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | ᠪᡠᠶᡝᠮᡝ ᡳ ᠰᡠᠨᡤᠠ ᡳ ᡳᠯᡤᠠᠨ ᡳ ᡵᠠᠰᡠ, 16:9 ᠠᠮᠠ 9:16. |
| `num_inference_steps` |  | integer | no | `27` | 2 – 40 | ᠰᠠᠮᡝᠨᡳ ᠵᠠᡴᡠᠨᠨᡳ ᠵᠠᠯᠠᠨ, ᠮᡠᠯᡥᡝ ᠵᠠᠯᠠᠨᡩᠣᠮᡝᠨᡳ ᠵᡝᠪᡝᠯᡝ ᠵᡠᠯᡝᠮᡝ. |
| `enable_safety_checker` |  | boolean | no | `false` |  | ᠵᠠᠰᡳᠮᡝ ᡳ ᠵᠠᠨ ᠠᠮᠠᠯᠠ ᡩᠠᠪᠠᠨ᠂ true ᠪᡝ ᠵᠠᠰᡳᠮᠪᡳ᠉ |
| `enable_output_safety_checker` |  | boolean | no | `false` |  | ᠪᡠᠶᡝᠮᡝ ᠰᡠᠨᡤᠠ ᡳ ᠠᠮᠠᠯᠠ ᡩᠠᠪᠠᠨ᠂ true ᠪᡝ ᠵᠠᠰᡳᠮᠪᡳ᠉ |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | ᠠᠮᠪᠠ ᠪᡠᠮᡝ ᡳ ᡥᡡᠯᠠᠨ ᠪᡝ ᠵᡠᠯᡝ ᠵᡠᠯᡝᠮᡝ᠉ |
| `acceleration` |  | enum (string) | no | `regular` | `none`, `regular` | ᠵᠠᠰᡳᠮᡝ ᡳ ᠪᠠᠶᠠᠨ᠂ 'regular' ᠵᠠᠨ ᠵᡠᠯᡝ ᡳᠰᡳᠨᠠᠮᠪᡳ᠉ ᠵᠠᠰᡳᠮᡝ ᠵᡝᠯᡤᡳ ᠪᡠᠶᡝᠮᡝ ᡳ ᠵᠠᠯᠠᠨ ᡩᡝ ᠰᡠᠮᠪᡝ ᠰᠠᠮᡝᠮᠪᡳ᠉ |
| `guidance_scale` |  | number | no | `3.5` | 1 – 10 | Classifier-free guidance ᡩᡝ ᠵᠠᠯᠠᠨ ᠵᡠᠯᡝᠮᡝ; ᠵᠠᠯᠠᠨ ᠣᠯᡥᠠ ᠣᠴᡳ ᡥᡡᠯᠠᠨ ᡩᡝ ᠵᡝᠯᡳᠨ ᠵᡠᠯᡝᠮᡝ. |
| `guidance_scale_2` |  | number | no | `4` | 1 – 10 | ᠵᠠᠭᠠᠨ ᠵᠠᠰᡳᠨ ᡳ ᠮᠣᡩᡝᠯ ᡳ ᡥᡡᠯᠠᠨ ᡩᡝ ᠠᠰᡠᠮᡝᠨ ᠵᠠᠰᡳᠮᠪᡳ᠉ |
| `shift` |  | number | no | `5` | 1 – 10 | ᠰᡠᠨᡤᠠ ᠰᡳᠯᡤᠠᠨ ᡳ ᠵᠠᠰᡳᠨ᠂ 1.0–10.0 ᠪᡝ ᠵᡝᠮᡝᠮᠪᡳ᠉ |
| `interpolator_model` |  | enum (string) | no | `film` | `none`, `film`, `rife` | ᡶᡳᠯᡝᠮᡝ ᡳ ᠵᠠᠯᠠᠮᡝ ᠵᠠᠰᡳᠨ᠄ None ᠪᡝ ᠰᠠᠮᡝᠮᠪᡳ᠂ ᠠᡴᡳ ᠵᠠᠰᡳᠮᡝ ᠮᠣᡩᡝᠯ ᠪᡝ ᠵᡝᠮᡝᠮᠪᡳ᠉ |
| `num_interpolated_frames` |  | integer | no | `1` | 0 – 4 | ᠵᡝᠨᡠ ᠪᡠᠶᡝᠮᡝ ᠵᡠᠶᡝᠨ ᡳ ᡳᠯᡳ ᡩᡝ 0–4 ᡶᡳᠯᡝᠮᡝ ᠣᠨᡩᠣᠮᠪᡳ᠉ |
| `adjust_fps_for_interpolation` |  | boolean | no | `true` |  | ᡶᡳᠯᡝᠮᡝ ᡳ ᠵᠠᠰᡳᠨ ᡳ ᠪᡠᠮᡝᠯᡝᠨ᠄ false ᠪᡝ ᠵᡝᠮᡝ ᠵᠠᠰᡳᠨ ᡩᡝ ᠰᡠᠮᡝᠮᠪᡳ᠂ true ᡩᡝ 1 ᡳ ᠵᠠᠰᡳᠮᡝᠨ ᡩᡝ ᠨᠠᠮᡠᠨ ᠵᠠᠰᡳᠮᠪᡳ᠉ |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | ᠪᡠᠶᡝᠮᡝ ᠰᡠᠨᡤᠠ ᡳ ᠰᡠᠮᠪᡝ ᡳ ᠵᠠᠰᡳᠨ᠂ ᠵᠠᠰᡳᠨ ᠵᠠᠯᠠᠮᡝ ᡶᡳᠯᡝ ᠨᠠᠮᠪᡳ᠉ |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | ᠰᡠᠨᡤᠠ ᠪᡳᡥᡝ ᡳ ᠵᠠᠰᡳᠨ᠂ balanced ᠵᠠᠰᡳᠨ ᠪᠠ ᠵᡝᠯᡤᡳ ᡳ ᠵᡝᠯᡤᡳ ᡳ ᠰᠠᠮᡝᠮᠪᡳ᠉ small ᠪᡝ ᠰᡠᠮᠪᡝ ᠪᠠ ᠵᠠᠯᠠᠨ ᡳ ᠪᡳᡥᡝ ᡩᡝ ᠰᠣᠩᡤᠣᠮᠪᡳ᠉ |
| `loras` |  | array of object {path, weight_name, scale, transformer} | no | `[]` |  | ᠵᡝᠯᡤᡳᠶᡝᠨ ᡩᡝ ᡤᠠᠶᠠᠮᡝ ᠪᠠᡳᠴᡳᠨᠠᠮᠪᡳ᠉ |
| `loras[].path` |  | string | yes |  |  | LoRA ᡳ ᡥᡡᠨᡩᡠᠨ ᡳ ᠪᠠ ᠪᡝ URL ᡝᠪᡨᡝᠯᡳ ᠵᡠᡤᡡᠨ ᠣᠪᡠᠮᡝ ᡨᠣᡴᡨᠣᠪᡠᡵᡝ᠈ |
| `loras[].weight_name` |  | string \| null | no |  |  | LoRA ᡠᠵᡝᠨ ᡳ ᡤᡝᠪᡠ᠂ Hugging Face ᡳ ᠠᠰᡥᡠᠨ ᡩᡝ 1 ᠣᠩᡤᠣᠯᠣ safetensors ᡶᡳᠯᡝ ᠪᡳᠰᡳᡵᡝ ᡩᡠᠪᡝᡩᡝ ᠪᠠᡳᡨᠠᠯᠠᡵᠠ᠉ ᡝᡵᡝ ᡤᡝᠪᡠ ᠪᡝ `path` ᡨᡝᡵᡝ ᡤᡝᠰᡝ ᠠᠰᡥᡠᠨ ᠪᡝ ᡨᡠᠸᠠᠪᡠᡵᡝ ᡩᡠᠪᡝᡩᡝ ᠪᠠᡳᡨᠠᠯᠠᡵᠠ᠉ |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | LoRA ᡳ ᡥᡡᠨᡩᡠᠨ ᠪᡝ ᡩᠠ ᠮᠣᠳᡝᠯ ᡩᡝ ᠠᠴᠠᠪᡠᡵᡝ ᠣᠩᡤᠣᠯᠣ ᠪᠠᡳᡨᠠᠯᠠᡵᠠ ᡩᠠᡥᡳᠨ᠈ |
| `loras[].transformer` |  | enum (string) | no | `high` | `high`, `low`, `both` | LoRA ᡶᡳᠯᡝᠮᡝ ᡠᠰᡳᠨᡳ ᡝᠮᡠᠯᡝᠨᡳ ᡝᠮᡠᠯᡝᠨ ᡩᡝ ᡝᠮᡤᡳᠯᡝᠮᡝ ᡤᡠᠮᡠᠨᠠᠮᡝ ᡝᠮᡤᡳᠯᡝᠮᡝᠨᡳ ᡠᠰᡳᠨᡳ ᡠᠨᡩᡝ ᡝᠮᡤᡳᠯᡝᠮᡝ ᡨᡝᠨᡝᠮᡝ᠂ 'high' ᡳᠨᡠ ᡩᠠᠯᠵᡳᠨᡤᠠ ᡠᠰᡳᠨᡳ᠂ 'low' ᡳᠨᡠ ᡨᡠᡵᡤᡠᠨ ᡠᠰᡳᠨᡳ᠂ ᡝᠮᡠ ᡠᠰᡳᠨᡳ ᡩᡝ ᡝᠮᡤᡳᠯᡝᠮᡝᠨᡳ ᡠᠯᡥᡠᠯᡝᠮᡝ ᡠᠨᡩᡝ ᠰᡝᠮᡝ 'both' ᠰᡳᠨᡝᠮᡝ. |
| `reverse_video` |  | boolean | no | `false` |  | ᠰᡠᠨᡤᠠ ᠪᠠᠨᠵᡳᠮᡝ ᡳ ᠪᡠᠮᡝᠯᡝᠨ᠂ true ᠪᡠᠮᡝᠯᡝᠨ ᠵᠠᠯᠠᠮᠪᡳ᠉ |

## Example input

Required parameters only:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

## 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/wan/v2.2-a14b/text-to-video/lora?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }'

# 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/wan/v2.2-a14b/text-to-video/lora?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }),
});
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 = {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/wan/v2.2-a14b/text-to-video/lora", 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": "wan/v2.2-a14b/text-to-video/lora",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
      },
      "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": "wan/v2.2-a14b/text-to-video/lora",
  "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": 507,
    "usd": "0.507",
    "charged": 507,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "output": {
    "video": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_name": "0-output.mp4",
      "file_size": 1843200
    },
    "prompt": "A close-up of a young woman smiling gently in the rain, raindrops glistening on her face and eyelashes. The video captures the delicate details of her expression and the water droplets, with soft light reflecting off her skin in the rainy atmosphere.",
    "seed": 42
  },
  "outputs": [
    {
      "type": "video",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_size": 1843200,
      "width": 1280,
      "height": 720,
      "duration": 5,
      "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 |
|---|---|---|
| `video` | object {url, content_type, file_name, file_size} | ᠪᡠᠶᡝᠮᡝ ᠵᡠᠴᡝᠨ ᡳ ᡶᡳᠯᡝ᠉ |
| `prompt` | string | ᠰᡠᠨᡤᠠ ᠪᡠᠶᡝᠮᡝ ᡳ ᡥᡡᠯᠠᠨ᠉ |
| `seed` | integer | ᠪᡠᠶᡝᠮᡝ ᡩᡝ ᠶᠠᠪᡠᡥᠠᠨ ᠪᠠᠨᠵᡳᠨᠠᠮᡝ᠉ |

## Related models

- [Wan v2.2 A14B Text-to-Image A14B with LoRAs](https://doitong.com/developers/models/wan/v2.2-a14b/text-to-image/lora.md) (`wan/v2.2-a14b/text-to-image/lora`): $0.05 / image
- [Wan v2.2 A14B Image-to-Video A14B with LoRAs](https://doitong.com/developers/models/wan/v2.2-a14b/image-to-video/lora.md) (`wan/v2.2-a14b/image-to-video/lora`): from $1.006 / run
- [Wan 3.0 Text to Video](https://doitong.com/developers/models/alibaba/wan-3.0/text-to-video.md) (`alibaba/wan-3.0/text-to-video`): from $0.05 / second
- [FLUX 3 Max Text to Video](https://doitong.com/developers/models/blackforestlabs/flux-3-max/text-to-video.md) (`blackforestlabs/flux-3-max/text-to-video`): from $0.0425 / second of output video
- [Grok Imagine Video 1.5 Text to Video](https://doitong.com/developers/models/xai/grok-imagine-video/v1.5/text-to-video.md) (`xai/grok-imagine-video/v1.5/text-to-video`): from $0.08 / second
- [Kling 3.0 Pro Text to Video](https://doitong.com/developers/models/kling-video/v3/pro/text-to-video.md) (`kling-video/v3/pro/text-to-video`): from $0.112 / second
- [LTX 2.5 Pro Text to Video](https://doitong.com/developers/models/lightricks/ltx-2.5/text-to-video/pro.md) (`lightricks/ltx-2.5/text-to-video/pro`): from $0.12 / second
- [MiniMax H3 Text to Video](https://doitong.com/developers/models/minimax/h3/text-to-video.md) (`minimax/h3/text-to-video`): from $0.05 / second

## Links

- HTML page: https://doitong.com/developers/models/wan/v2.2-a14b/text-to-video/lora
- 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=wan/v2.2-a14b/text-to-video/lora
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/wan/v2.2-a14b/text-to-video/lora