Instructions to use ipetrousov/weedcrop_svm_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use ipetrousov/weedcrop_svm_classifier with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("ipetrousov/weedcrop_svm_classifier", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
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Download README.md from ipetrousov/weedcrop_svm_classifier: direct link, hf CLI and curl.
- Browser
- Download file 164 Bytes
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https://huggingface.co/ipetrousov/weedcrop_svm_classifier/resolve/main/README.md
- Command line
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hf download hf://ipetrousov/weedcrop_svm_classifier/README.md
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curl -L -o README.md https://huggingface.co/ipetrousov/weedcrop_svm_classifier/resolve/main/README.md
164 Bytes
| license: mit | |
| language: | |
| - en | |
| metrics: | |
| - f1 | |
| - precision | |
| - recall | |
| pipeline_tag: image-classification | |
| tags: | |
| - python | |
| - SVM | |
| - farming | |
| - vision | |
| - sklearn | |
| - scikit | |