Instructions to use theguaz/rembrantsito with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use theguaz/rembrantsito with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("theguaz/rembrantsito", 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 theguaz/rembrantsito: direct link, hf CLI and curl.
- Browser
- Download file 246 MB
-
https://huggingface.co/theguaz/rembrantsito/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://theguaz/rembrantsito/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/theguaz/rembrantsito/resolve/main/text_encoder/pytorch_model.bin
246 MB
- Xet hash:
- a02b82dfd0af67b965d61022caeec19c1b7f3fbc6e45dee7e79da12f2f4579a3
- Size of remote file:
- 246 MB
- SHA256:
- ff7764d75c3b3b1ce944d251f0038db1211a44762658e4a2e734faee80d2c028
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