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pca_gp_vkils59
fabiencasenave/pca_gp_vkils59
pca_gp_vkils59 is a graph machine learning model from fabiencasenave. Use it for the graph machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
The code used to train this model is given in train.py.
Access
Public
Updated Aug 10, 2025
Repo size
18.4 MB
Likes
2
Public
Repo makeup
Click a slice to open those files.
.joblib18.4 MB · 100%
At a glance
- Task
- Graph Machine Learning
- License
- mit
- Access
- Public
- Created
- Aug 10, 2025
- Updated
- Aug 10, 2025
- SHA
- c9b0ffd8
Datasets
Model card
From the Hugging Face model README
PCA-GP model for VKILS59 dataset
The code used to train this model is given in train.py.
Install
pip install git+https://huggingface.co/fabiencasenave/pca_gp_vkils59
Use
from datasets import load_dataset
from plaid.bridges.huggingface_bridge import huggingface_dataset_to_plaid
import pca_gp_vkils59
model = pca_gp_vkils59.load()
hf_dataset = load_dataset("PLAID-datasets/VKI-LS59", split="all_samples")
ids_test = hf_dataset.description["split"]['test']
dataset_test, _ = huggingface_dataset_to_plaid(hf_dataset, ids = ids_test, processes_number = 6, verbose = True)
print("Check that 'mach' field is not present in test dataset: dataset_test[0].get_field('mach', base_name='Base_2_2') =", dataset_test[0].get_field('mach', base_name='Base_2_2'))
print("Run prediction...")
dataset_pred = model.predict(dataset_test)
print("Check that 'mach' field is now present in pred dataset: dataset_pred[0].get_field('mach', base_name='Base_2_2') =", dataset_pred[0].get_field('mach', base_name='Base_2_2'))
- Task
- Graph Machine Learning
- License
- mit
- Languages
- en
- Created
- Aug 10, 2025
- Updated
- Aug 10, 2025