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fal
/
AuraFlow

Text-to-Image
Diffusers
Safetensors
AuraFlowPipeline
Model card Files Files and versions
xet
Community
31

Instructions to use fal/AuraFlow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Diffusers

    How to use fal/AuraFlow with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("fal/AuraFlow", dtype=torch.bfloat16, device_map="cuda")
    
    prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
    image = pipe(prompt).images[0]
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • Draw Things
  • DiffusionBee
AuraFlow / tokenizer
2.39 MB
Ctrl+K
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  • 3 contributors
History: 6 commits
isidentical's picture
isidentical
Add fp16 variants to speedup loading and relax memory constraints (#15)
f16d500 verified almost 2 years ago
  • added_tokens.json
    2.59 kB
    Rename added_tokens.json to tokenizer/added_tokens.json almost 2 years ago
  • special_tokens_map.json
    2.68 kB
    Add fp16 variants to speedup loading and relax memory constraints (#15) almost 2 years ago
  • tokenizer.json
    1.86 MB
    Rename tokenizer.json to tokenizer/tokenizer.json almost 2 years ago
  • tokenizer.model
    500 kB
    xet
    Rename tokenizer.model to tokenizer/tokenizer.model almost 2 years ago
  • tokenizer_config.json
    21 kB
    Rename tokenizer_config.json to tokenizer/tokenizer_config.json almost 2 years ago