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Yntec
/
Abased

Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
anime
style
BDZ888
stable-diffusion
stable-diffusion-diffusers
Model card Files Files and versions
xet
Community
2

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

  • Libraries
  • Diffusers

    How to use Yntec/Abased with Diffusers:

    pip install -U diffusers transformers accelerate
    import torch
    from diffusers import DiffusionPipeline
    
    # switch to "mps" for apple devices
    pipe = DiffusionPipeline.from_pretrained("Yntec/Abased", 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
Abased / tokenizer
1.59 MB
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  • 1 contributor
History: 2 commits
Yntec's picture
Yntec
Delete tokenizer/added_tokens.json
ed5d1a3 over 2 years ago
  • merges.txt
    525 kB
    Adding `diffusers` weights of this model (#1) over 2 years ago
  • special_tokens_map.json
    133 Bytes
    Adding `diffusers` weights of this model (#1) over 2 years ago
  • tokenizer_config.json
    904 Bytes
    Adding `diffusers` weights of this model (#1) over 2 years ago
  • vocab.json
    1.06 MB
    Adding `diffusers` weights of this model (#1) over 2 years ago