Instructions to use nyu-visionx/RAE-dinov2-wReg-base-ViTXL-n08-i512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nyu-visionx/RAE-dinov2-wReg-base-ViTXL-n08-i512 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nyu-visionx/RAE-dinov2-wReg-base-ViTXL-n08-i512", 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
- Xet hash:
- d6006256dfb500fe22c9d84416f2c98e715d7b882a8493fa062288fe098e4a4f
- Size of remote file:
- 2.02 GB
- SHA256:
- b29ffdc68fa85049c561c38bc8e8c483614d8b00be85532b0a53669cd257429a
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