Feature Extraction
Transformers
Safetensors
English
remote-sensing
earth-observation
self-supervised-learning
satellite
multispectral
convnext
mae
mmearth
mp-mae
Instructions to use BiliSakura/MMEarth-transformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BiliSakura/MMEarth-transformers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BiliSakura/MMEarth-transformers")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BiliSakura/MMEarth-transformers", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- mmearth-convnextv2-atto-all-mod-100k-128-uncertainty-112x16
- mmearth-convnextv2-atto-all-mod-1m-128-uncertainty-112x16
- mmearth-convnextv2-atto-all-mod-1m-64-uncertainty-56x8
- mmearth-convnextv2-atto-all-mod-1m-64-unweighted-56x8
- mmearth-convnextv2-atto-img-mod-1m-64-uncertainty-56x8
- mmearth-convnextv2-atto-pix-mod-1m-64-uncertainty-56x8
- mmearth-convnextv2-atto-rgb-1m-128-uncertainty-112x16
- mmearth-convnextv2-atto-rgb-1m-64-uncertainty-56x8
- mmearth-convnextv2-atto-s2-1m-64-uncertainty-56x8
- mmearth-convnextv2-tiny-all-mod-1m-64-uncertainty-56x8
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- 6.42 kB