Instructions to use Muapi/naraka-wan2.1-14b-t2v with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/naraka-wan2.1-14b-t2v with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wan-ai/Wan2.1-T2V-14B-Diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/naraka-wan2.1-14b-t2v") prompt = "A man with short gray hair plays a red electric guitar." output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Naraka/奈羅花 | Wan2.1 14B T2V
Base model: Wan Video 14B t2v Trained words: Naraka, anime-style girl. The image features an anime-style character with long, white hair that flows down to the shoulders. The hair is styled in a loose, flowing manner, giving it a soft and ethereal appearance. The character has red eyes, which stand out prominently against their pale skin. They have pointed ears and two small, purple horns on either side of the head. The character is wearing a traditional-looking outfit with a deep red color. The upper part of the outfit includes a high collar with intricate gold embroidery on the chest area. The sleeves are long and flowy, adding to the character's graceful and elegant appearance. The character is also wearing a headpiece that resembles a fox mask, complete with pointed ears and a small tail, suggesting a connection to a mythical or fantasy theme.
🧠 Usage (Python)
🔑 Get your MUAPI key from muapi.ai/access-keys
import requests, os
url = "https://api.muapi.ai/api/v1/wan21_t2v"
headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")}
payload = {
"prompt": "masterpiece, best quality",
"lora_model": "naraka奈羅花-wan21-14b-t2v",
"lora_strength": 1.0,
"width": 832,
"height": 480,
"num_frames": 81
}
print(requests.post(url, headers=headers, json=payload).json())
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