Diffusers
Safetensors
ConsistencyModelPipeline
generative model
unconditional image generation
consistency-model
Instructions to use openai/diffusers-cd_imagenet64_lpips with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use openai/diffusers-cd_imagenet64_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_imagenet64_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
Download unet/diffusion_pytorch_model.bin from openai/diffusers-cd_imagenet64_lpips: direct link, hf CLI and curl.
- Browser
- Download file 1.18 GB
-
https://huggingface.co/openai/diffusers-cd_imagenet64_lpips/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://openai/diffusers-cd_imagenet64_lpips/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/openai/diffusers-cd_imagenet64_lpips/resolve/main/unet/diffusion_pytorch_model.bin
1.18 GB
- Xet hash:
- 01ff10da20c246b1f7c438de718ef2202d62c2dc863be85647d3e4d99ac1cd72
- Size of remote file:
- 1.18 GB
- SHA256:
- 4d2790d566436e5174ecd59e2292c0e03be03e0697ba0cdcd18bfa41d3b5034e
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