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
| { | |
| "tag": "Edge_IIoTset__BiLSTM__FedAvg__non_iid", | |
| "dataset": "Edge_IIoTset", | |
| "model": "BiLSTM", | |
| "fl_algo": "FedAvg", | |
| "partition": "non_iid", | |
| "n_clients": 30, | |
| "n_rounds": 30, | |
| "total_time_s": 1057.2, | |
| "model_params": 79233, | |
| "model_mb": 0.3169, | |
| "final": { | |
| "accuracy": 0.84042, | |
| "precision": 0.8221233913701741, | |
| "recall": 0.86882, | |
| "f1_binary": 0.8448269155970439, | |
| "f1_macro": 0.840291185258382, | |
| "f1_weighted": 0.840291185258382, | |
| "fpr": 0.18798, | |
| "auc_roc": 0.9326115422000001, | |
| "threshold": 0.4610846936702728 | |
| } | |
| } |