Instructions to use kxic/eschernet-4dof with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kxic/eschernet-4dof with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kxic/eschernet-4dof", 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 image_encoder/pytorch_model.bin from kxic/eschernet-4dof: direct link, hf CLI and curl.
- Browser
- Download file 112 MB
-
https://huggingface.co/kxic/eschernet-4dof/resolve/main/image_encoder/pytorch_model.bin
- Command line
-
hf download hf://kxic/eschernet-4dof/image_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/kxic/eschernet-4dof/resolve/main/image_encoder/pytorch_model.bin
112 MB
- Xet hash:
- 116169f8fc42a2e56f784925b2aa8352edc11b0a4b8c143eb1f6a8b652d1b327
- Size of remote file:
- 112 MB
- SHA256:
- 8e1707986b80f76c402a2f11fade8cb0406b1100a8540e9052e76839c58c3dfa
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