Instructions to use KamiyabAli/frames with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use KamiyabAli/frames 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("KamiyabAli/frames") prompt = "FRM$ a majestic mountain range with snow-capped peaks in the background, illuminated by the setting sun. The sky is a beautiful mix of oranges, pinks, and purples, creating a stunning backdrop for the majestic peaks." image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Add generated example
#2
by KamiyabAli - opened
Generated example for model KamiyabAli/frames.
Prompt: FRM$ a realistic mountain landscape during the day, captured from a camera. A winding river flows through a lush green valley, with only one towering mountain in the distance covered in snow. The rest of the landscape is green and vibrant, contrasting with the white peak. The sky is partly cloudy, with soft, rolling clouds casting shadows over the terrain. Sunlight filters through the clouds, creating dynamic lighting across the valley, while the river glistens in the daylight. The snow-covered mountain stands as a striking focal point against the serene, natural surroundings.
KamiyabAli changed pull request status to merged