Instructions to use skaura/ercc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use skaura/ercc with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("skaura/ercc", 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
Download vae/diffusion_pytorch_model.bin from skaura/ercc: direct link, hf CLI and curl.
- Browser
- Download file 335 MB
-
https://huggingface.co/skaura/ercc/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://skaura/ercc/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/skaura/ercc/resolve/main/vae/diffusion_pytorch_model.bin
335 MB
- Xet hash:
- fda118b27471c5e9cb464c10f93e32c8c66ab6a041640798d549e58fc4778e92
- Size of remote file:
- 335 MB
- SHA256:
- 69f0a1935267388cd33dbdec70ab3df2117d4748d2bc106b68a410b207ce32b7
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