Instructions to use logo-wizard/logo-diffusion-checkpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use logo-wizard/logo-diffusion-checkpoint 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("logo-wizard/logo-diffusion-checkpoint") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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README.md
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@@ -17,7 +17,7 @@ We recommend using this model with the following prompt template:
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**negative:** "low quality, worst quality, bad composition, extra digit, fewer digits, text, inscription, watermark, label, asymmetric"
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Some other recommendations:
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**num_inference_steps**
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**guidance_scale** = *7.5*
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**height** = *768*
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**width** = *768*
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**negative:** "low quality, worst quality, bad composition, extra digit, fewer digits, text, inscription, watermark, label, asymmetric"
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Some other recommendations:
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**num_inference_steps** = *30*
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**guidance_scale** = *7.5*
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**height** = *768*
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**width** = *768*
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