Text-to-Image
Diffusers
Safetensors
English
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Instructions to use wavymulder/Analog-Diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wavymulder/Analog-Diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wavymulder/Analog-Diffusion", 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 wavymulder/Analog-Diffusion: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/wavymulder/Analog-Diffusion/resolve/refs%2Fpr%2F3/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://wavymulder/Analog-Diffusion@refs/pr/3/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/wavymulder/Analog-Diffusion/resolve/refs%2Fpr%2F3/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 93d1a02ef949f1221408fa5fb9d3c2f60096161985b7fd6dc1ca804bba5bd541
- Size of remote file:
- 492 MB
- SHA256:
- 2eac1795aca396db76dc02aeab649aac7ca620a13979a188d282575a52b995b5
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