Instructions to use jimmycarter/krea2-turbo-bbox with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jimmycarter/krea2-turbo-bbox with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jimmycarter/krea2-turbo-bbox", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
krea2-turbo-bbox / epoch-1-step-5228 /transformer /diffusion_pytorch_model-00003-of-00003.safetensors
- Xet hash:
- 2e4d43963ff7050d75959e74f44cc257a94e856573d4eb7364cbc41095524868
- Size of remote file:
- 5.89 GB
- SHA256:
- 15619091b122f4d2ea4aa75a8299f50f85c505646bcdd120f58448bba5ac9628
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