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va1bhavagrawa1
/
seethrough3d

Text-to-Image
Diffusers
English
controllable text-to-image generation
diffusion models
3D layout control
occlusion reasoning
Model card Files Files and versions
xet
Community
1

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
  • Draw Things
  • DiffusionBee
seethrough3d / train /src
Ctrl+K
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  • 2 contributors
History: 6 commits
va1bhavagrawa1's picture
va1bhavagrawa1
corrected imports
d485900 3 months ago
  • __pycache__
    corrected imports 3 months ago
  • __init__.py
    0 Bytes
    first commit 3 months ago
  • jsonl_datasets.py
    12.3 kB
    working demo, organized files 3 months ago
  • layers.py
    16.2 kB
    working training code with both the stages 3 months ago
  • lora_helper.py
    12.3 kB
    first commit 3 months ago
  • pipeline.py
    37 kB
    working demo, organized files 3 months ago
  • prompt_helper.py
    0 Bytes
    working training code with both the stages 3 months ago
  • transformer_flux.py
    24.8 kB
    working training code with both the stages 3 months ago