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dreamcomputing
/
Flux-Dev-8-step

Text-to-Image
Diffusers
Safetensors
FluxPipeline
Model card Files Files and versions
xet
Community

Instructions to use dreamcomputing/Flux-Dev-8-step with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use dreamcomputing/Flux-Dev-8-step with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("dreamcomputing/Flux-Dev-8-step", 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
Flux-Dev-8-step
36.5 GB
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  • 1 contributor
History: 13 commits
Chris
Upload model_index.json
4c42663 verified about 1 year ago
  • scheduler
    Upload scheduler_config.json about 1 year ago
  • text_encoder
    Upload 2 files about 1 year ago
  • text_encoder_2
    Upload 5 files about 1 year ago
  • tokenizer
    Upload 8 files about 1 year ago
  • tokenizer_2
    Upload 8 files about 1 year ago
  • transformer
    Upload diffusion_pytorch_model-00003-of-00003.safetensors about 1 year ago
  • vae
    Upload 2 files about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • model_index.json
    536 Bytes
    Upload model_index.json about 1 year ago