Instructions to use snake7gun/Bernini-R-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use snake7gun/Bernini-R-tiny with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("snake7gun/Bernini-R-tiny", 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
Download vae/diffusion_pytorch_model.safetensors from snake7gun/Bernini-R-tiny: direct link, hf CLI and curl.
- Browser
- Download file 89.8 kB
-
https://huggingface.co/snake7gun/Bernini-R-tiny/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://snake7gun/Bernini-R-tiny/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/snake7gun/Bernini-R-tiny/resolve/main/vae/diffusion_pytorch_model.safetensors
89.8 kB
- Xet hash:
- db4192e43cb53ac27fa24211b49ad67bbd600d8d20c77a2d43471b21825b543d
- Size of remote file:
- 89.8 kB
- SHA256:
- 3e640338657b50fcb01ade5dec6b934736f5ece2383011f8e0ba14f6600b393f
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