Instructions to use xiangjx/MuPaD-512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xiangjx/MuPaD-512 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("xiangjx/MuPaD-512", 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
Update demo.py
Browse files
demo.py
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@@ -16,7 +16,7 @@ def test_pipeline():
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# TODO: Replace this with your actual Hugging Face Write/Read token
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hf_token = ""
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repo_id = "xiangjx/MuPaD-
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# 1. Load Diffusion Pipeline
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print(f"Loading pipeline from {repo_id}...")
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# TODO: Replace this with your actual Hugging Face Write/Read token
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hf_token = ""
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repo_id = "xiangjx/MuPaD-512"
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# 1. Load Diffusion Pipeline
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print(f"Loading pipeline from {repo_id}...")
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