Feature Extraction
Transformers
Safetensors
English
remote-sensing
earth-observation
satellite
multispectral
spatiotemporal
foundation-model
mae
prithvi
hls
vision
Instructions to use BiliSakura/Prithvi-EO-2.0-transformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BiliSakura/Prithvi-EO-2.0-transformers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BiliSakura/Prithvi-EO-2.0-transformers")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BiliSakura/Prithvi-EO-2.0-transformers", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 526 Bytes
d324dd8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | {
"image_processor_type": "PrithviImageProcessor",
"num_channels": 6,
"num_frames": 4,
"size": {
"height": 224,
"width": 224
},
"do_resize": false,
"do_rescale": false,
"do_normalize": true,
"do_convert_rgb": false,
"image_mean": [
1087.0,
1342.0,
1433.0,
2734.0,
1958.0,
1363.0
],
"image_std": [
2248.0,
2179.0,
2178.0,
1850.0,
1242.0,
1049.0
],
"auto_map": {
"AutoImageProcessor": "image_processing_prithvi.PrithviImageProcessor"
}
}
|