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:
- eab96365afa78e56adb024f604a2c335acf8a60f0bf0d7035a6eea9def9e7568
- Size of remote file:
- 1.4 kB
- SHA256:
- 95d5da8195335d4ea322bbf2d1a3e2e6db077cf77404469c5cb95a451f7e56fa
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