Instructions to use FloydianSound/Nixeu_Diffusion_v1-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FloydianSound/Nixeu_Diffusion_v1-5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FloydianSound/Nixeu_Diffusion_v1-5", 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 FloydianSound/Nixeu_Diffusion_v1-5: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/FloydianSound/Nixeu_Diffusion_v1-5/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://FloydianSound/Nixeu_Diffusion_v1-5/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/FloydianSound/Nixeu_Diffusion_v1-5/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 730c68e10cfd53fef2a78d7fb7105ae78d1bcf75ceae74a005c5d301b3836a2c
- Size of remote file:
- 492 MB
- SHA256:
- 0ba894995e4d793f0982e63e3eb66b83ecaf49a6c4cfe6a45dd9a9e6416baea5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.