Image Feature Extraction
Transformers
Safetensors
resnet
SAR
RADAR
EO
backbone
ocean
wind
sentinel-1
Instructions to use galeio-research/OceanSAR-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use galeio-research/OceanSAR-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="galeio-research/OceanSAR-1")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("galeio-research/OceanSAR-1") model = AutoModel.from_pretrained("galeio-research/OceanSAR-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "ResNetModel" | |
| ], | |
| "depths": [ | |
| 3, | |
| 4, | |
| 6, | |
| 3 | |
| ], | |
| "downsample_in_bottleneck": false, | |
| "downsample_in_first_stage": false, | |
| "embedding_size": 64, | |
| "hidden_act": "relu", | |
| "hidden_sizes": [ | |
| 256, | |
| 512, | |
| 1024, | |
| 2048 | |
| ], | |
| "layer_type": "bottleneck", | |
| "model_type": "resnet", | |
| "num_channels": 1, | |
| "out_features": [ | |
| "stage4" | |
| ], | |
| "out_indices": [ | |
| 4 | |
| ], | |
| "stage_names": [ | |
| "stem", | |
| "stage1", | |
| "stage2", | |
| "stage3", | |
| "stage4" | |
| ], | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.51.1" | |
| } | |