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 checkpoint-120000/optimizer.bin from erkam/sd-clevr-scene-graph: direct link, hf CLI and curl.
- Browser
- Download file 6.85 MB
-
https://huggingface.co/erkam/sd-clevr-scene-graph/resolve/main/checkpoint-120000/optimizer.bin
- Command line
-
hf download hf://erkam/sd-clevr-scene-graph/checkpoint-120000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/erkam/sd-clevr-scene-graph/resolve/main/checkpoint-120000/optimizer.bin
6.85 MB
- Xet hash:
- 8d8cf856a92125725f51bcf4082603cd39cf0f1f8854b5486ba1ba78662a921b
- Size of remote file:
- 6.85 MB
- SHA256:
- c5bb3a2f2c03e0f88b3415e0f25b43b7b7ff33171c3baad628bd3024166d889c
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