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: 585 Bytes
15b3eec ca32ecd 15b3eec ca32ecd 15b3eec ca32ecd 15b3eec ca32ecd 15b3eec | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | {
"name": "Edge_IIoTset",
"n_train": 400000,
"n_test": 100000,
"n_features": 21,
"features": [
"tcp.dstport",
"tcp.srcport",
"tcp.ack",
"tcp.seq",
"tcp.len",
"tcp.ack_raw",
"mqtt.msgtype",
"mqtt.len",
"tcp.connection.syn",
"tcp.connection.rst",
"mqtt.conflag.cleansess",
"tcp.connection.fin",
"mqtt.topic_len",
"mqtt.ver",
"mqtt.proto_len",
"tcp.connection.synack",
"tcp.flags.ack",
"arp.opcode",
"http.content_length",
"http.response",
"arp.hw.size"
],
"n_clients": 30,
"alpha": 0.5
} |