Instructions to use nousr/sd-v1-5-ema with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nousr/sd-v1-5-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("nousr/sd-v1-5-ema", torch_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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 4d58d962d5090b5351808762533fd1892fa8990c1d0b200606949eb773ab9bc9
- Size of remote file:
- 335 MB
- SHA256:
- 3fc88475c3f6ee7d0336b95ab32b28c983f5550e949c48c7af0b7e39d30f6f5e
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