datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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.DoD-Instruction-8010-01-Information-Network-Transport
🌐 DoD Information Network Transport
Maintainer: Terry Eppler
Owner: US Federal Government
Source: DoD Instruction 8010.01
Dataset Size: question-answer records
Source Effective Date: September 10, 2018
Source Organization: Office of the DoD Chief Information Officer
Source Ownership: United States Department of Defense
📋 Overview
Dataset Summary
The DoD Information Network Transport Question-Answer Dataset contains document-grounded… See the full description on the dataset page: https://huggingface.co/datasets/leeroy-jankins/DoD-Instruction-8010-01-Information-Network-Transport.qemu_networking
Qemu Networking from Claude Haiku 4.5
A synthetic instruction-tuning dataset covering QEMU networking concepts, generated using Claude Haiku 4.5.
Dataset Summary
Total rows: 75
Topic: QEMU virtual networking
Difficulty distribution: Easy, Intermediate, Advanced
278 unique tags across networking subtopics
Splits
train: 75 rows
Columns
id: Stable entry ID
instruction: Instruction text for fine-tuning
input: Original prompt/question
output:… See the full description on the dataset page: https://huggingface.co/datasets/creeperdatasets/qemu_networking.for_Conceal-NetworkDataset is meant to train OPEN_LLAMA_v2, a converted JSON version is also available
Usage
exemple with llama.cpp & open_llama_3b_v2
Finetune:
finetune --model-base "C:\llama.cpp\models\open_llama_3b_v2_f32.gguf" --train-data "C:\llama.cpp\docs\conceal\conceal56_llama.txt" --lora-out lora-CCX_01.gguf --save-every 0 --threads 16 --ctx 256 --rope-freq-base 10000 --rope-freq-scale 1.0 --batch 1 --grad-acc 1 --adam-iter 256 --adam-alpha 0.00025 --lora-r… See the full description on the dataset page: https://huggingface.co/datasets/Acktarius/for_Conceal-Network.