Instructions to use erkam/sd-clevr-scene-graph with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use erkam/sd-clevr-scene-graph 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-scene-graph") 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
Download image_1.png from erkam/sd-clevr-scene-graph: direct link, hf CLI and curl.
- Browser
- Download file 426 kB
-
https://huggingface.co/erkam/sd-clevr-scene-graph/resolve/main/image_1.png
- Command line
-
hf download hf://erkam/sd-clevr-scene-graph/image_1.png
-
curl -L -o image_1.png https://huggingface.co/erkam/sd-clevr-scene-graph/resolve/main/image_1.png
426 kB

- Xet hash:
- d83943e8a5d01aaaf96fbf510e268577ebb43b41c9d6d34f291848230698b439
- Size of remote file:
- 426 kB
- SHA256:
- 4d9566824cee0738498d3aed46054a3dae5529e845cc83c8e6926e7c6ba88434
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