Instructions to use dg845/diffusers-cm_edm_imagenet64_ema with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dg845/diffusers-cm_edm_imagenet64_ema with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("dg845/diffusers-cm_edm_imagenet64_ema", 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
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This is a version of the `edm_imagenet64_ema` [EDM](https://arxiv.org/pdf/2206.00364.pdf) model checkpoint developed by OpenAI and released as part of the [consistency models](https://arxiv.org/pdf/2303.01469.pdf) [code repo](https://github.com/openai/consistency_models) intended to be compatible with the experimental `KarrasEDMPipeline`.
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