Instructions to use erkam/sd-clevr-sg2layout-objects_cap-e2e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use erkam/sd-clevr-sg2layout-objects_cap-e2e 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-2", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("erkam/sd-clevr-sg2layout-objects_cap-e2e") 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
- Xet hash:
- 0c44bdd03978acacd06e5995be84f6d06b664d31d989e820c14c2f2067e5dec1
- Size of remote file:
- 137 MB
- SHA256:
- ccfeae859594e76e8ff1ff72d4d0d860323d86a3a2cb7c0c7b4a05642b5946d7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.