Instructions to use prof-freakenstein/anurag-s-stable-diffusion-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use prof-freakenstein/anurag-s-stable-diffusion-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("prof-freakenstein/anurag-s-stable-diffusion-model", 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 prof-freakenstein/anurag-s-stable-diffusion-model: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/prof-freakenstein/anurag-s-stable-diffusion-model/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://prof-freakenstein/anurag-s-stable-diffusion-model/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/prof-freakenstein/anurag-s-stable-diffusion-model/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- 7b18a20a85de82f2418df67bcbc1e08ecd07e5099472e1ca7de572aa2556547b
- Size of remote file:
- 246 MB
- SHA256:
- 8f695fb99a950cb9f291b78cff38eb29c43f173584983eac4c65030ee48338fe
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.