Instructions to use dfrer/nanasa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dfrer/nanasa with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1-base", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("dfrer/nanasa") prompt = "Man sleeping next to clock" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download 7381798.jpeg from dfrer/nanasa: direct link, hf CLI and curl.
- Browser
- Download file 12.1 kB
-
https://huggingface.co/dfrer/nanasa/resolve/main/7381798.jpeg
- Command line
-
hf download hf://dfrer/nanasa/7381798.jpeg
-
curl -L -o 7381798.jpeg https://huggingface.co/dfrer/nanasa/resolve/main/7381798.jpeg
12.1 kB

- Xet hash:
- 977c4636c7b06c6028d145af4b99c5553058a5c548f645c6baad245ee0e308d4
- Size of remote file:
- 12.1 kB
- SHA256:
- d10772d5c035c4f997210a04a8d4bb233b03aafad566cddfd2be137e011d0c62
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.