Instructions to use nyu-visionx/webssl300m_decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nyu-visionx/webssl300m_decoder with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-image" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("image-to-image", model="nyu-visionx/webssl300m_decoder")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForPreTraining processor = AutoImageProcessor.from_pretrained("nyu-visionx/webssl300m_decoder") model = AutoModelForPreTraining.from_pretrained("nyu-visionx/webssl300m_decoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add model card for Scale-RAE (#1)
Verified signature- Add model card for Scale-RAE (5422b55b65c4a25125672ff410a179212cdfcef4) Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>0e6a28d
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Fix config.json: Change hidden_size from 1152 to 1024 to match WebSSL DINO encoder output dimension
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Upload config.json with huggingface_hub
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Upload model.pt with huggingface_hub
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initial commit
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