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Base model: Wan Video 14B t2v Trained words: photo background, real world location
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Quellenbeschreibung
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Base model: Wan Video 14B t2v Trained words: photo background, real world location
🔑 Get your MUAPI key from muapi.ai/access-keys
Quellen
1 QuelleVerifiziert 26. Sept.
Modellartefakte
1 Artefaktphoto-background-2d-compositing.safetensors
safetensors · 293 MB · SHA-256 3d546a0ac3c2…0187 · Hugging Face
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2 Auszüge--- license: openrail++ library_name: diffusers base_model: wan-ai/Wan2.1-T2V-14B-Diffusers tags: - lora - text-to-video - wan - wan2.1 - wan-video-14b-t2v pipeline_tag: text-to-video --- # Photo Background - 2d Compositing｜写真背景・二次元合成  **Base model**: Wan Video 14B t2v **Trained words**: photo background, real world location ## 🧠 Usage (Python) 🔑 **Get your MUAPI key** from [muapi.ai/access-keys](https://muapi.ai/access-keys) ```python 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": "photo-background-2d-compositing写真背景二次元合成", "lora_strength": 1.0, "width": 832, "height": 480, "num_frames": 81 } print(requests.post(url, headers=headers, json=payload).json()) ```
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": "photo-background-2d-compositing写真背景二次元合成",
"lora_strength": 1.0,
"width": 832,
"height": 480,
"num_frames": 81
}
print(requests.post(url, headers=headers, json=payload).json())
Source context: 20 downloads · 0 likes · Pipeline text-to-video · Library diffusers · Repo Muapi/photo-background-2d-compositing