Instructions to use Jovie/Digital with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jovie/Digital with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Jovie/Digital") prompt = "\"symmetry!! portrait of curvaceous alien in the style of horizon zero dawn, machine face, intricate, elegant, highly detailed, digital painting, artstation, concept art, smooth, sharp focus, illustration, art by artgerm and greg rutkowski and alphonse mucha" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Create README.md
Browse files
README.md
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---
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tags:
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- text-to-image
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- stable-diffusion
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- lora
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- diffusers
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- template:sd-lora
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base_model: black-forest-labs/FLUX.1-dev
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instance_prompt: anime
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widget:
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- text: >-
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"symmetry!! portrait of curvaceous alien in the style of horizon zero dawn,
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machine face, intricate, elegant, highly detailed, digital painting,
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artstation, concept art, smooth, sharp focus, illustration, art by artgerm
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and greg rutkowski and alphonse mucha
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output:
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url: images/example_rndh30ve1.png
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---
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# Piotr model style
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<Gallery />
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## Model description
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## Trigger words
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You should use `` to trigger the image generation.
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## Download model
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Weights for this model are available in Safetensors format.
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[Download](/Jovie/Piotr/tree/main) them in the Files & versions tab.
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