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
| 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 | |
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| <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: | |
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