Diffusers
ConsistencyModelPipeline
generative model
unconditional image generation
consistency-model
Instructions to use openai/diffusers-cd_cat256_lpips with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use openai/diffusers-cd_cat256_lpips with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("openai/diffusers-cd_cat256_lpips", 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
- Xet hash:
- 03a7b0cf21d6a072ce12494d221a2907bc1076fab44623c9430604e60ae371da
- Size of remote file:
- 2.11 GB
- SHA256:
- 915d3dbcfeb9e64af7a38f435f060a8e486cd53fbaaea879655492735ad11297
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