datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
sage-control-plane-llm-workloadscontrol-the-planetThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v2.1",
"robot_type": "so100_follower",
"total_episodes": 2,
"total_frames": 1929,
"total_tasks": 1,
"total_videos": 2,
"total_chunks": 1,
"chunks_size": 1000,
"fps": 30,
"splits": {
"train": "0:2"
},
"data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/lilkm/control-the-planet.sage-control-plane-workloads
SAGE Control Plane Workloads
Workload configurations for benchmarking Control Plane scheduling policies.
Usage
from datasets import load_dataset
workloads = load_dataset("intellistream/sage-control-plane-workloads")
sage-control-plane-hybrid-workloadssage-control-plane-benchmarknetwork-control-plane-data-plane-coherence-risk-v0.1
What this repo is for
Detect when routing looks correct but forwarding fails.
This is a classic outage pattern:
routing tables show reachability
traceroute path deviates
blackholes appear
ping success falls
packet loss rises
A model that detects this early can cut incident time fast.