Instructions to use Muapi/editanything with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/editanything 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("Lightricks/LTX-Video", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/editanything") 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
- Draw Things
File size: 797 Bytes
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license: openrail++
library_name: diffusers
base_model: Lightricks/LTX-Video
tags:
- lora
- text-to-video
- ltx
- ltx-video
- ltxv-2.3
pipeline_tag: text-to-video
---
# EditAnything

**Base model**: LTXV 2.3
**Trained words**:
## 🧠 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/ltx_lora_video"
headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")}
payload = {
"prompt": "masterpiece, best quality",
"lora_model": "editanything",
"lora_strength": 1.0,
"width": 768,
"height": 512,
"num_frames": 97
}
print(requests.post(url, headers=headers, json=payload).json())
```
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