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
Commit Β·
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inference/config.py
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# Available Checkpoint weights (dropdown options)
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CHECKPOINT_NAMES = [
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# ββ Blender Backend Server URLs βββββββββββββββββββββββββββββββββββββββββββββββ
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# Available Checkpoint weights (dropdown options)
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CHECKPOINT_NAMES = [
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# ββ Blender Backend Server URLs βββββββββββββββββββββββββββββββββββββββββββββββ
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