Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use digiplay/SweetMuse_diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use digiplay/SweetMuse_diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("digiplay/SweetMuse_diffusers", 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
Update README.md
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README.md
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Model info : https://civitai.com/models/81668/sweetmuse
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Sample image
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Model info : https://civitai.com/models/81668/sweetmuse
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Sample image
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Recently,
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diffusers converter I don't why,Model shows error,
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if you use this model in your diffusers,
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show some AutoencoderKL errors,
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don't worry,
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please use the codes below,
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you can still generate images :)
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```
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modelid="digiplay/SweetMuse_diffusers"
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from diffusers.models import AutoencoderKL
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vae = AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse")
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pipe = DiffusionPipeline.from_pretrained(modelid, vae=vae)
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```
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