Instructions to use philz1337x/cybervision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use philz1337x/cybervision with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("philz1337x/cybervision", 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 philz1337x/cybervision: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/philz1337x/cybervision/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://philz1337x/cybervision/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/philz1337x/cybervision/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 2991153a38f3095c06b354074432e7edb53128470224a0bd5f4076f26710d89e
- Size of remote file:
- 492 MB
- SHA256:
- 79bdd651655d6698c67aecc430fb25deb83cca1336f876b23289c1a01f6df06c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.