Instructions to use dicksondickson/graphis-01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dicksondickson/graphis-01 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("dicksondickson/graphis-01") prompt = "graphis-01 cityscape" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Commit ·
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README.md
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## Model description
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This fun LoRA model generates stylized graphics with a flat, textured look featuring smooth, grainy gradients. It was trained on a custom dataset of my own digital illustrations showcasing graphic shapes on various paper textures. For optimal results, use the trigger word "graphis-01" in your prompts. Experiment with different LoRA weightings to achieve various stylistic effects. Recommended weightings range from 0.6 to 1.6 (when using ComfyUI). For best results, pair this model with an artistic base model such as Zavy Chroma XL. Image-to-image
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## Trigger words
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## Model description
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This fun LoRA model generates stylized graphics with a flat, textured look featuring smooth, grainy gradients. It was trained on a custom dataset of my own digital illustrations showcasing graphic shapes on various paper textures. For optimal results, use the trigger word "graphis-01" in your prompts. Experiment with different LoRA weightings to achieve various stylistic effects. Recommended weightings range from 0.6 to 1.6 (when using ComfyUI). For best results, pair this model with an artistic base model such as Zavy Chroma XL. Image-to-image generations yeiled some very interesting results as well. Have fun!
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## Trigger words
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