Text-to-Image
Diffusers
TensorBoard
Safetensors
GGUF
StableDiffusionXLPipeline
stable-diffusion-xl
stable-diffusion-xl-diffusers
image-to-image
lora
Instructions to use kiel2/Kiel-2-Image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kiel2/Kiel-2-Image with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("kiel2/Kiel-2-Image") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Update README.md
Browse files
README.md
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---
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## 🚀 Recommended Usage & Parameters
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-
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* **Resolution:** 1024 × 1024 pixels (Native SDXL resolution)
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* **Sampling Steps:** 25 – 35 steps
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* **Sampler:** DPM++ 2M Karras, DPM++ SDE Karras, or Euler a
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).images[0]
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image.save("generated_image.png")
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Image-to-Image (StableDiffusionXLImg2ImgPipeline)
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Python
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import torch
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import gc
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---
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## 🚀 Recommended Usage & Parameters
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* **Resolution:** 1024 × 1024 pixels (Native SDXL resolution)
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* **Sampling Steps:** 25 – 35 steps
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* **Sampler:** DPM++ 2M Karras, DPM++ SDE Karras, or Euler a
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).images[0]
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image.save("generated_image.png")
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```
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### 2. Image-to-Image (StableDiffusionXLImg2ImgPipeline)
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Python
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import torch
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import gc
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