datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
netopsbench-trace
NetOpsBench Agent Traces
This dataset contains sanitized NetOpsBench benchmark trace artifacts.
The legacy cross-model snapshot contains minimal-deepagent runs for
MiniMax M3, DeepSeek V4 Pro, Kimi K2.6, and OpenAI GPT-5.5 on the XS, Small,
Medium, and Large CLOS profiles.
The NetOpsBench v0.2 release adds a separately versioned
minimal-deepagent / deepseek-v4-pro snapshot across all seven built-in
profiles: XS, Small, Medium, Large, Xlarge, Fat-tree K=8, and Fat-tree K=12.
It… See the full description on the dataset page: https://huggingface.co/datasets/yyyyyt/netopsbench-trace.lens-network-traffic-generation
Lens Network Traffic Generation Benchmark
Network-traffic generation data used to evaluate Lens, a knowledge-guided foundation model
for network traffic (TMLR). Each of the 8 source datasets is a HuggingFace config,
with train / validation / test splits and a unified schema.
This is the generation counterpart of the classification benchmark
Charles59/lens-network-traffic.
ℹ️ All data is derived from publicly available academic traffic datasets
obtained via the NetBench… See the full description on the dataset page: https://huggingface.co/datasets/Charles59/lens-network-traffic-generation.quantum-networking-and-distributed
Neura Parse — Quantum Networking, Repeaters & Distributed Quantum Computing
A systems-frontier vertical on connecting quantum devices: entanglement distribution and distillation, quantum repeaters, quantum-internet protocol stacks, quantum memories/transduction, and modular/distributed quantum computing (nonlocal gates, circuit knitting across nodes, blind/verifiable delegated computation). Covers protocol and simulation methods used with tools such as NetSquid and SeQUeNCe… See the full description on the dataset page: https://huggingface.co/datasets/Neura-parse/quantum-networking-and-distributed.Building_External_Networks_Ecosystems_Theory
Building External Networks Ecosystems — Theory
This corpus was automatically generated by the Deku Corpus Builder for use in RAG-based AI applications.
Dataset Structure
Each record contains:
text: The content text
source_url: Original source URL
source_title: Title of the source document
source_domain: Domain of the source
license_type: License classification (e.g. public_domain, cc_by, cc_by_sa)
attribution_required: Boolean — True for CC BY / CC BY-SA and other… See the full description on the dataset page: https://huggingface.co/datasets/PhillyMac/Building_External_Networks_Ecosystems_Theory.Building_External_Networks_Ecosystems_Practical
Building External Networks Ecosystems — Practical
This corpus was automatically generated by the Deku Corpus Builder for use in RAG-based AI applications.
Dataset Structure
Each record contains:
text: The content text
source_url: Original source URL
source_title: Title of the source document
source_domain: Domain of the source
license_type: License classification (e.g. public_domain, cc_by, cc_by_sa)
attribution_required: Boolean — True for CC BY / CC BY-SA and other… See the full description on the dataset page: https://huggingface.co/datasets/PhillyMac/Building_External_Networks_Ecosystems_Practical.