Text-to-Image
Diffusers
Safetensors
StableDiffusionXLPipeline
stable-diffusion-xl
stable-diffusion-xl-diffusers
diffusers-training
lora
Instructions to use magnusdtd/ViStableDiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use magnusdtd/ViStableDiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("magnusdtd/ViStableDiffusion") 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: apache-2.0 | |
| library_name: diffusers | |
| tags: | |
| - stable-diffusion-xl | |
| - stable-diffusion-xl-diffusers | |
| - text-to-image | |
| - diffusers | |
| - diffusers-training | |
| - lora | |
| - stable-diffusion-xl | |
| - stable-diffusion-xl-diffusers | |
| - text-to-image | |
| - diffusers | |
| - diffusers-training | |
| - lora | |
| ## Sample Outputs of the Fine-Tuned Model | |
| ### Output 1 | |
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| ### Output 2 | |
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| ### Output 3 | |
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| ### Output 4 | |
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