Instructions to use Muapi/pony-diffusion-v6-xl-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/pony-diffusion-v6-xl-2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Muapi/pony-diffusion-v6-xl-2", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| license: openrail++ | |
| library_name: diffusers | |
| tags: | |
| - text-to-image | |
| - stable-diffusion | |
| - sdxl | |
| pipeline_tag: text-to-image | |
| # Pony Diffusion V6 XL 2 | |
| **Base model**: SDXL | |
| Originally published by [stablediffusionapi](https://huggingface.co/stablediffusionapi). | |
| Mirrored here for use with [muapi.ai](https://muapi.ai) — a unified API for generative media. | |
| ## 🧠 Usage via muapi.ai | |
| 🔑 **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/sdxl-image" | |
| headers = {"Content-Type": "application/json", "x-api-key": os.getenv("MUAPIAPP_API_KEY")} | |
| payload = { | |
| "prompt": "masterpiece, best quality", | |
| "model": "pony-diffusion-v6-xl-2", | |
| "width": 1024, | |
| "height": 1024, | |
| "num_images": 1 | |
| } | |
| print(requests.post(url, headers=headers, json=payload).json()) | |
| ``` | |