Instructions to use nyu-visionx/RAE-dinov2-wReg-large-ViTXL-n08 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nyu-visionx/RAE-dinov2-wReg-large-ViTXL-n08 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-large-ViTXL-n08", 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:
- 67068e4bd39ed202e6ca3b8138a34e27b5cda57ee77c51b03a0c2e20be4f6029
- Size of remote file:
- 2.88 GB
- SHA256:
- 0f4e8338d995026119dcaaf6d341ec59e67a4419171da25654c66ccf002fc158
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