Image Segmentation
Transformers
Safetensors
actu
feature-extraction
climate
geospatial
remote-sensing
spatiotemporal
multi-modal
earth-observation
time-series
hydrology
custom_code
Instructions to use DarthReca/actu-direction-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DarthReca/actu-direction-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="DarthReca/actu-direction-classification", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DarthReca/actu-direction-classification", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 298bb57c8d3c616717566e6cc37e058fb0be46846a10951e7155b28509f0c605
- Size of remote file:
- 890 MB
- SHA256:
- a3e210955dbff46e240bbdfbb39a7200021ce9774d6753194e6f117fac03ef46
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