Instructions to use uf/analogMadness_v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use uf/analogMadness_v5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("uf/analogMadness_v5", 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 uf/analogMadness_v5: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/uf/analogMadness_v5/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://uf/analogMadness_v5/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/uf/analogMadness_v5/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- f155f83fe53697d34e09fc91d0c8e7ceb3c5eb55a59c7925243c2f3bd6de5e0c
- Size of remote file:
- 492 MB
- SHA256:
- 6a9d519242dc50ff1ba86535b61022d6bb5a89961eef7e7f3a167873653327ad
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