Instructions to use Quantumbraid/amber with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Quantumbraid/amber with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krea/Krea-2-Raw", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Quantumbraid/amber") prompt = "A hyper-realistic portrait of @mb3r as a futuristic cybernetic deity floating in a void of liquid gold and neon circuitry." image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- fd53d4ecf2a2f30536da2e8fdecc2ab115e9a27b0de180fba6f5c5ebd5b7a76b
- Size of remote file:
- 1.26 MB
- SHA256:
- 8da0011e93e83ae5b1f39b9f2e5c318f79d066a7ea8c3a7555030a6de6693d9c
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