Feature Extraction
Transformers
Safetensors
English
remote-sensing
earth-observation
self-supervised-learning
sentinel-2
sentinel-1
multispectral
sar
vision
ssl4eo
mae
moco
dino
data2vec
vit
resnet
Instructions to use BiliSakura/SSL4EO-S12-transformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BiliSakura/SSL4EO-S12-transformers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BiliSakura/SSL4EO-S12-transformers")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BiliSakura/SSL4EO-S12-transformers", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download ssl4eo-vit-small-patch16-s2c-data2vec/preprocessor_config.json from BiliSakura/SSL4EO-S12-transformers: direct link, hf CLI and curl.
- Browser
- Download file 251 Bytes
-
https://huggingface.co/BiliSakura/SSL4EO-S12-transformers/resolve/main/ssl4eo-vit-small-patch16-s2c-data2vec/preprocessor_config.json
- Command line
-
hf download hf://BiliSakura/SSL4EO-S12-transformers/ssl4eo-vit-small-patch16-s2c-data2vec/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/BiliSakura/SSL4EO-S12-transformers/resolve/main/ssl4eo-vit-small-patch16-s2c-data2vec/preprocessor_config.json
251 Bytes
| { | |
| "image_processor_type": "SSL4EOData2VecImageProcessor", | |
| "size": { | |
| "height": 224, | |
| "width": 224 | |
| }, | |
| "do_resize": false, | |
| "do_rescale": true, | |
| "do_normalize": false, | |
| "do_convert_rgb": false, | |
| "rescale_factor": 0.00392156862745098 | |
| } | |