Instructions to use nyu-visionx/RAE-dinov2-wReg-small-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-small-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-small-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
Upload folder using huggingface_hub
#1
by bytetriper - opened
- config.json +0 -0
- conversion_metadata.json +12 -0
- diffusion_pytorch_model.safetensors +3 -0
config.json
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conversion_metadata.json
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{
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"source": "/data/boyang/models",
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"encoder_cls": "dinov2",
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"encoder_name_or_path": "facebook/dinov2-with-registers-small",
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"decoder_checkpoint": "decoders/dinov2/wReg_small/ViTXL_n08/model.pt",
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"stats_checkpoint": "stats/dinov2/wReg_small/imagenet1k/stat.pt",
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"variant": "ViTXL_n08",
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"dataset_name": "imagenet1k",
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"decoder_config_name": "ViTXL",
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"missing_decoder_keys": [],
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"unexpected_decoder_keys": []
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}
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diffusion_pytorch_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:7f51209b98da22c46ea238f9b7bc8b5f6108017753cf1bcff9e0d2442e97f239
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size 1748739848
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