Instructions to use JabaleNurAdnan/CS_Checkpoints_Dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use JabaleNurAdnan/CS_Checkpoints_Dataset with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://JabaleNurAdnan/CS_Checkpoints_Dataset") - Notebooks
- Google Colab
- Kaggle
File size: 555 Bytes
483efc5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"tag": "Edge_IIoTset__BiLSTM__FedProx__iid",
"dataset": "Edge_IIoTset",
"model": "BiLSTM",
"fl_algo": "FedProx",
"partition": "iid",
"n_clients": 30,
"n_rounds": 30,
"total_time_s": 8366.9,
"model_params": 79233,
"model_mb": 0.3169,
"final": {
"accuracy": 0.77257,
"precision": 0.8185345331307702,
"recall": 0.70042,
"f1_binary": 0.7548849490758205,
"f1_macro": 0.7713798900114914,
"f1_weighted": 0.7713798900114913,
"fpr": 0.15528,
"auc_roc": 0.8748885938,
"threshold": 0.4885738492012024
}
} |