Instructions to use antikpatel128/OUTPUT_DIR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use antikpatel128/OUTPUT_DIR 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("antikpatel128/OUTPUT_DIR") 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
File size: 946 Bytes
60953d4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ---
license: other
tags:
- text-to-image
- stable-diffusion
- lora
- diffusers
base_model: stabilityai/stable-diffusion-xl-base-1.0
instance_prompt:
widget:
- text:
---
# Slider SDXL - LoRA

<h2 id="heading-2">SDXL ONLY</h2><ul><li><p>weight: <strong>0 to 5.0</strong></p></li><li><p>positive: <strong>more realistic</strong></p></li><li><p>negative: <strong>less realistic, cartoon, painting, etc</strong></p></li></ul><p></p><p>I noticed the more bizarre your prompt gets, the more SDXL wants to turn it into a cartoon. This helps give you the ability to adjust the level of realism in a photo. All images were generated without refiner. I refuse. </p><p></p><p>If you like my work, I am not asking for coffee, but a kind review is always appreciated.<br /><br /></p>
## Image examples for the model:




|