Feature Extraction
Transformers
Safetensors
English
closp
remote-sensing
text-to-image-retrieval
multimodal
geospatial
SAR
multispectral
crisis-management
earth-observation
contrastive-learning
custom_code
Instructions to use DarthReca/CLOSP-RN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DarthReca/CLOSP-RN with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="DarthReca/CLOSP-RN", trust_remote_code=True, device_map="auto")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DarthReca/CLOSP-RN", trust_remote_code=True, dtype="auto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac123d0854ab8a8d296ecdddccd5306ff125611b063fcd2fead070cef2fac70e
- Size of remote file:
- 299 MB
- SHA256:
- 175d51c3c2e53061999945c9eb2beb159191a4e5e2061a9de34407825bf7bf91
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