Instructions to use backnotprop/crash-report-framed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use backnotprop/crash-report-framed with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("backnotprop/crash-report-framed") prompt = "a close up of a colorful circular object with a city in the background in the style of <s0><s1>, explosion of data fragments, isolated on white background, dendrites, 3d cell shaded, london, view from slightly above, atsmospheric, looking partly to the left, fully symmetrical, giant explosion, datamoshed" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee

- Xet hash:
- 8e324705b353337709a4ffa625eb83292d9fdfe6b6c5e5360077f7db7c2907b8
- Size of remote file:
- 2.19 MB
- SHA256:
- 4a3f9668036e1de8ac6eb706eb35be112de851d50fd7f8458753ed09ee6b8bca
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