Image Classification
Transformers
Safetensors
resnet
EO
SAR
sentinel-1
wind
ocean
earth-observation
remote-sensing
satellite-imagery
synthetic-aperture-radar
foundation-model
linear-probing
oceanography
marine-forecasting
open-source
ocean-wind
Instructions to use galeio-research/OceanSAR-1-wind with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use galeio-research/OceanSAR-1-wind with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="galeio-research/OceanSAR-1-wind") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("galeio-research/OceanSAR-1-wind") model = AutoModelForImageClassification.from_pretrained("galeio-research/OceanSAR-1-wind") - Notebooks
- Google Colab
- Kaggle
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- sentinel-1
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- ocean
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---
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# Model Card for Nereus-SAR-1-Wind
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## Model
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### Model Description
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Nereus-SAR-1-Wind is a linear probing head for wind speed prediction built on top of the Nereus-SAR-1 foundation model. It leverages the powerful features extracted by Nereus-SAR-1 to accurately predict wind speed from Synthetic Aperture Radar (SAR) imagery.
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- sentinel-1
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- wind
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- ocean
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- earth-observation
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- remote-sensing
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- satellite-imagery
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- synthetic-aperture-radar
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- foundation-model
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- linear-probing
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- oceanography
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- marine-forecasting
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- open-source
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- ocean-wind
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---
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# Model Card for Nereus-SAR-1-Wind
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## Model Description
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Nereus-SAR-1-Wind is a linear probing head for wind speed prediction built on top of the Nereus-SAR-1 foundation model. It leverages the powerful features extracted by Nereus-SAR-1 to accurately predict wind speed from Synthetic Aperture Radar (SAR) imagery.
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