Instructions to use Muapi/parkour-it-i-wan-2.1-i2v-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/parkour-it-i-wan-2.1-i2v-lora 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/parkour-it-i-wan-2.1-i2v-lora") 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
Parkour it I Wan 2.1 I2V LoRa
Base model: Wan Video 14B i2v 480p Trained words: p4rk0uR, From a first-person p4rk0uR perspective, the video shows running across a flat, tiled rooftop under a bright blue sky, surrounded by city buildings. Approaching the edge, a p4rk0uR jump is executed across a gap to land on a lower rooftop level. The p4rk0uR movement continues forward on this new roof surface., From a first-person p4rk0uR perspective, starting exactly from this image view, take a running leap across the rooftop gap.
๐ง Usage (Python)
๐ 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": "parkour-it-i-wan-21-i2v-lora",
"lora_strength": 1.0,
"width": 832,
"height": 480,
"num_frames": 81
}
print(requests.post(url, headers=headers, json=payload).json())
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