Feature Extraction
Transformers
Safetensors
English
remote-sensing
earth-observation
vision
croma
sentinel-1
sentinel-2
multimodal
Instructions to use BiliSakura/CROMA-transformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BiliSakura/CROMA-transformers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="BiliSakura/CROMA-transformers")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BiliSakura/CROMA-transformers", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "CromaModel" | |
| ], | |
| "model_type": "croma", | |
| "dtype": "float32", | |
| "transformers_version": "5.0.0", | |
| "hidden_size": 1024, | |
| "num_hidden_layers": 24, | |
| "num_attention_heads": 16, | |
| "patch_size": 8, | |
| "image_size": 120, | |
| "sar_channels": 2, | |
| "optical_channels": 12, | |
| "modality": "both", | |
| "hidden_dropout_prob": 0.0, | |
| "layer_norm_eps": 1e-05, | |
| "initializer_range": 0.02, | |
| "num_patches": 225, | |
| "auto_map": { | |
| "AutoConfig": "modeling_croma.CromaConfig", | |
| "AutoModel": "modeling_croma.CromaModel" | |
| }, | |
| "custom_pipelines": { | |
| "croma-feature-extraction": { | |
| "impl": "pipeline_croma.CROMAImageFeatureExtractionPipeline", | |
| "pt": [ | |
| "AutoModel" | |
| ] | |
| } | |
| } | |
| } |