Instructions to use Saurabh4509/Model_45 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Saurabh4509/Model_45 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Saurabh4509/Model_45", 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 unet/diffusion_pytorch_model.bin from Saurabh4509/Model_45: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/Saurabh4509/Model_45/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://Saurabh4509/Model_45/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/Saurabh4509/Model_45/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- 2825d7bd5dfdd15fbfdd0d9b373d5ccc59b98fb86a3d334aabf3374ccd95a22a
- Size of remote file:
- 3.44 GB
- SHA256:
- 4d253d0938e5d47d96799d97fb0be72f241cc5cebf95464e651d62965538ba1c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.