Instructions to use sinkinai/GhostMix-V2-BakedVae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sinkinai/GhostMix-V2-BakedVae with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("sinkinai/GhostMix-V2-BakedVae", 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 text_encoder/pytorch_model.bin from sinkinai/GhostMix-V2-BakedVae: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/sinkinai/GhostMix-V2-BakedVae/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://sinkinai/GhostMix-V2-BakedVae/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sinkinai/GhostMix-V2-BakedVae/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- d6617a14097fa34a1b34d8cdacc0a2f8967e886a158eb556a5b053d75265fbe9
- Size of remote file:
- 492 MB
- SHA256:
- c4d1ad79ea48561d7fdec2ec9870b857443542f2f76ff24c9aabc7c59f800816
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.