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:
- 7caa77e5f25256b48a75c7e725fa86c68c613531eac53d214c6b694fca9c2a13
- Size of remote file:
- 2.02 GB
- SHA256:
- 017ddbdf26ecde51e1cf410ba74d4c71f0620992dfcf544f33c45447a94b351a
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