Instructions to use Muapi/natori-sana-wan2.1-14b-t2v with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/natori-sana-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/natori-sana-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
Natori Sana/εεγγͺ | Wan2.1 14B T2V
Base model: Wan Video 14B t2v Trained words: Natori Sana, anime-style girl. The image features an anime-style character with long, light brown hair that flows down past the shoulders. The character has a gentle, slightly melancholic expression, with red eyes that convey a sense of sadness or contemplation. The character is wearing a pink headband adorned with heart-shaped decorations and bunny ears, adding a playful touch to the overall appearance.The character's outfit consists of a white blouse with puffy sleeves and a pink apron over it. The apron has a large heart design on the front, complementing the headband and adding a cohesive theme to the attire.The character also wears white knee-high socks and white shoes, which complement the overall pastel theme.
π§ Usage (Python)
π 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": "natori-sanaεεγγͺ-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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