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akrao9
/
Boomer-T2I

Text-to-Image
Diffusers
Safetensors
PyTorch
English
BoomerPipeline
diffusion
linear-attention
Model card Files Files and versions
xet
Community

Instructions to use akrao9/Boomer-T2I with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use akrao9/Boomer-T2I with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("akrao9/Boomer-T2I", 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

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  • scheduler
    Add Boomer FLA fine-tuned checkpoint (step 055000, ema weights) about 2 months ago
  • transformer
    Update transformer weights (step 65000, ema, bf16) about 1 month ago
  • .gitattributes
    84 Bytes
    Add Boomer FLA fine-tuned checkpoint (step 055000, ema weights) about 2 months ago
  • README.md
    9.2 kB
    Update README.md 29 days ago
  • STORKScheduler.py
    76.4 kB
    Add Boomer FLA fine-tuned checkpoint (step 055000, ema weights) about 2 months ago
  • model_index.json
    141 Bytes
    Add Boomer FLA fine-tuned checkpoint (step 055000, ema weights) about 2 months ago
  • modeling_boomer_fla.py
    54.8 kB
    Add Boomer FLA checkpoint (step 055000, ema weights, bf16) about 2 months ago
  • pipeline_boomer.py
    13.8 kB
    Update pipeline_boomer.py about 2 months ago
  • scheduling_boomer_stork.py
    4.07 kB
    Add Boomer FLA fine-tuned checkpoint (step 055000, ema weights) about 2 months ago