Instructions to use glif-loradex-trainer/chrysolite_Imagelite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use glif-loradex-trainer/chrysolite_Imagelite 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("glif-loradex-trainer/chrysolite_Imagelite") prompt = "foggy, waterfall, trees Negative, Monochromatic, Greyscale, Low Quality, Pixelated, Old, Scenery, Image.lite.png" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Imagelite
Model trained with AI Toolkit by Ostris under the Glif Loradex program by Glif user chrysolite.

- Prompt
- foggy, waterfall, trees Negative, Monochromatic, Greyscale, Low Quality, Pixelated, Old, Scenery, Image.lite.png

- Prompt
- mountain, lakes Negative, Monochromatic, Greyscale, Low Quality, Pixelated, Old, Scenery, Image.lite.png

- Prompt
- Waterfall, mountain, forest, landscape Negative, Monochromatic, Greyscale, Low Quality, Pixelated, Old, Scenery, Image.lite.png
Trigger words
You should use Negative, Monochromatic, Greyscale, Low Quality, Pixelated, Old, Scenery, Image.lite.png to trigger the image generation.
Download model
Weights for this model are available in Safetensors format. Download them in the Files & versions tab.
License
This model is licensed under the flux-1-dev-non-commercial-license.
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Model tree for glif-loradex-trainer/chrysolite_Imagelite
Base model
black-forest-labs/FLUX.1-dev