Text-to-Image
Diffusers
English
controllable text-to-image generation
diffusion models
3D layout control
occlusion reasoning
Instructions to use va1bhavagrawa1/seethrough3d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use va1bhavagrawa1/seethrough3d with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("va1bhavagrawa1/seethrough3d", 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
Download inference/example0.jpg from va1bhavagrawa1/seethrough3d: direct link, hf CLI and curl.
- Browser
- Download file 241 kB
-
https://huggingface.co/va1bhavagrawa1/seethrough3d/resolve/main/inference/example0.jpg
- Command line
-
hf download hf://va1bhavagrawa1/seethrough3d/inference/example0.jpg
-
curl -L -o example0.jpg https://huggingface.co/va1bhavagrawa1/seethrough3d/resolve/main/inference/example0.jpg
241 kB

- Xet hash:
- fae7413938d5a07724e88836eaa2d2890d313d26b0a69b4ca888a608f525e0f2
- Size of remote file:
- 241 kB
- SHA256:
- 1b0860511e9f3a42945af1e05a882b4ca3cf33eb485dd3bb116cbd564dd3ad1a
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