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:
- 165afd5d6d714a718824da646873e10f8354efd84595255a68f683ff7fb5376d
- Size of remote file:
- 45.7 MB
- SHA256:
- 4ee43cd7d50c28b0957f45632710a2b6274cb62c7b5f3247775b8ca275b109f2
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