Text-to-Image
Diffusers
English
stable-diffusion
lora
dalle-3
dalle
deepvision
template:sd-lora
HelpingAI
HelpingAI-PixelCraft
Instructions to use OEvortex/HelpingAI-PixelCraft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use OEvortex/HelpingAI-PixelCraft with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fluently/Fluently-XL-Final", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("OEvortex/HelpingAI-PixelCraft") prompt = "a close up of a fire breathing pokemon figure, digital art, trending on polycount, real life charmander, sparks flying, photo-realistic unreal engine, pokemon in the wild" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Update README.md
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README.md
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lighting, high detail, concept art, behance, ray tracing
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output:
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url: images/b7ad0f38-5d2a-48cd-b7d4-b94be1d23c40.jpg
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base_model:
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instance_prompt: <lora:Dall-e_3_0.3-v2-000003>
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license: mit
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language:
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lighting, high detail, concept art, behance, ray tracing
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output:
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url: images/b7ad0f38-5d2a-48cd-b7d4-b94be1d23c40.jpg
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base_model: bonniebelle/juggernaut-xl-v5
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instance_prompt: <lora:Dall-e_3_0.3-v2-000003>
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license: mit
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language:
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