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resnet50_sentinel2_all_dino

Hugging Face model torchgeo/resnet50_sentinel2_all_dino (image-classification)

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What's in it

Data offered llm-inferred
pretrained ResNet-50 image-classification weights (Sentinel-2, DINO self-supervised)
Coverage llm-inferred
Global
Formats docs-verified
timm-loadable PyTorch model weights
Access docs-verified
Open licence (CC-BY-4.0); no API key required per ENTRY auth metadata; not hosted by any Inference Provider

Useful for

Use cases llm-inferred
Pretrained backbone for transfer learning on Sentinel-2 imagery for site land-cover baselines · Feature extraction from Sentinel-2 tiles for BNG habitat baseline mapping · Scene classification of catchment imagery for planning or constraints screening
Audience llm-inferred
GIS analysts · ecologists · geospatial ML engineers · remote sensing specialists

Limitations

Constraints llm-inferred
Not deployed by any Inference Provider, so no hosted inference endpoint · Weights are third-party (SSL4EO-S12) and modified for timm; upstream requirements not verified · DOCS give no input band specification, accuracy metrics or class list · Requires a local PyTorch/timm environment to run
Licence
cc-by-4.0
Authentication
No API key required (repository README, auto-extracted; check upstream requirements)
GitHub stars
Unknown
Last commit
Unknown
Last successful page check
14/10/2026
Page health
healthy
Package
Not recorded
Verification
Not independently verified

Provenance & evidence

Verified 2026-10-15 via HF API: exists; 912 downloads/30d, 2 likes.

Metadata observed 14/10/2026 · research sweep: manual-2026-10-15 (Hugging Face models)