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
- Draw Things
- DiffusionBee
| [general] | |
| shuffle_caption = false | |
| caption_extension = '.txt' | |
| keep_tokens = 1 | |
| [[datasets]] | |
| resolution = 1024 | |
| batch_size = 1 | |
| keep_tokens = 1 | |
| [[datasets.subsets]] | |
| image_dir = '/root/fluxgym/datasets/frames' | |
| class_tokens = 'FRM$' | |
| num_repeats = 10 |