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
Update config.json
Browse files- config.json +5 -1
config.json
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"torch_dtype": "float32",
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"transformers_version": "4.53.2",
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"use_climate_branch": false,
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"use_dem_input": false
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}
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"torch_dtype": "float32",
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"transformers_version": "4.53.2",
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"use_climate_branch": false,
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"use_dem_input": false,
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"auto_map": {
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"AutoModel": "modeling_actu.ACTUForImageSegmentation",
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"AutoConfig": "modeling_actu.ACTUConfig"
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}
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}
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