datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
drone-router-dataset-navlink-v2
NAVLINK Drone Router Dataset — Round 2 Snapshot
This dataset is the exact training/eval snapshot used for the best reviewed overnight FunctionGemma/NAVLINK run (“10-epoch run 2”), which reached:
Tool-call exact-match accuracy (line 1): 95.2%
476 / 500 correct
0 safety violations
This is the dataset snapshot before the later waypoint-copy-heavy augmentation that regressed performance.
Files
navlink_train_run2.jsonl — 4,307 training examples
navlink_test_run2.jsonl —… See the full description on the dataset page: https://huggingface.co/datasets/llama-farm/drone-router-dataset-navlink-v2.router-assistant-tool-calling-en-es
Router Assistant Tool Calling EN-ES
Synthetic English and Spanish conversations for supervised fine-tuning of a small,
local router assistant. The assistant answers brief social turns, obtains current
network facts through tools, handles tool failures, and asks for confirmation before
restarting the router or disabling WAN internet access.
Dataset size
Split
Conversations
Assistant completions
Train
11,066
21,242
Validation
984
1,890
Test
926
1,769… See the full description on the dataset page: https://huggingface.co/datasets/Lucasllfs/router-assistant-tool-calling-en-es.Support-Ticket-Router-12K-Cleaned
🔥 Support-Ticket-Router-12K-Cleaned
This dataset is a cleaned and structured version of real-world-like customer support messages designed for intent classification and routing tasks in SaaS / IT support systems.
It is intended for training and evaluating LLM-based or classical NLP intent classifiers for automated customer support ticket routing.
🧪 Data Source
This dataset is synthetically generated using GPT-4-class models (GPT-4 / GPT-4o-style prompting) with… See the full description on the dataset page: https://huggingface.co/datasets/cngchis/Support-Ticket-Router-12K-Cleaned.NOESIS-1M-reasoning-router-code-math-psych-opus47-deepseek4-qwen36-gemini31-r1-gpt54
NOESIS DORA SFT Dataset
Multilingual supervised fine-tuning dataset built for the NOESIS QwQ+DeepSeek-R1 MoE pipeline.
Released as part of the NOESIS Professional Multilingual Dubbing Automation Platform(framework: DHCF-FNO — Deterministic Hybrid Control Framework for Frozen Neural Operators).
Founder: Ilia Bolotnikov
Organization: AMAImedia.com
X (Twitter): @AMAImediacom
LinkedIn: Ilia Bolotnikov
Telegram: @djbionicl
NOESIS version: v14.8-NT89
Build date: 2026-04… See the full description on the dataset page: https://huggingface.co/datasets/SMH-DEV-AI/NOESIS-1M-reasoning-router-code-math-psych-opus47-deepseek4-qwen36-gemini31-r1-gpt54.minimind-fr-router-data
minimind-fr-router-data
sft_router.jsonl (17,467) + router_eval.jsonl (2,567 held-out) —
conversations schema, assistant.content is one of creative devops coding electronics general unsafe. Built by scripts/convert_router.py
from the specialist SFT sets + lmsys/toxic-chat. See the
minimind-fr-router model card.
Built from
lmsys/toxic-chat
Format: line-delimited JSON. SFT rows use MiniMind's SFTDataset schema —
{"conversations": [{role, content, reasoning_content… See the full description on the dataset page: https://huggingface.co/datasets/yassinsiouda/minimind-fr-router-data.yo-router-data
yo-router-data
Synthetic training data for yo, a macOS tool router fine-tuned from FunctionGemma-270M.
Each row maps one plain-English utterance to exactly one function call over a fixed menu of 10
read-only macOS tools.
This is the dataset that produced lagna360/yo-router-270m
(56.2% → 95.2% tool accuracy). Generator, eval harness and full results:
github.com/lagna360/yo.
It is fully reproducible. Everything here is regenerable byte-for-byte from
data/generate.py at seed 17 —… See the full description on the dataset page: https://huggingface.co/datasets/lagna360/yo-router-data.algocean-router
algocean-router
질의·보안 등급·사용 가능한 모델 목록을 받아 어느 모델로 보낼지(또는 기권) 정하도록 가르치는 LoRA SFT 데이터셋입니다.
파이프라인 첫 관문입니다. 답을 만들지 않고, 근거도 보지 않습니다. 누가 이 일을 할지만 정합니다.
규모
파일
행 수
router.jsonl
150,000
router.eval.jsonl
2,000
형식: JSONL, messages 3턴
언어: 한국어 약 70% · 영어 약 30%
어디에 쓰나요
멀티 모델 게이트웨이의 난이도·보안 기반 라우팅
후보 모델 레지스트리를 읽고 스펙(컨텍스트·등급·비용 등)으로 선택
조건 맞는 모델이 없으면 ABSTAIN
모델 id는 샘플마다 가명으로 바뀌어 있어, 이름 암기가 아니라 스펙 추론을 배우게 됩니다.
어떤 모델에 LoRA 하나요
베이스:… See the full description on the dataset page: https://huggingface.co/datasets/Algocean/algocean-router.arcnav-router-v1-dataset
arcnav-router-v1 — training dataset (iter v1i)
Synthetic dataset for training the arcnav-router-v1 drone chat-to-JSON command router. Built for the arc-uas platform.
Files
canonical_v1i.jsonl — 6,659 training examples across 26 buckets
gold_v3.jsonl — 329 hand-curated eval examples (held out from training)
system_prompt_v1.md — 728-token system prompt the model is trained against
Schema
Each record is a single conversation:
{
"messages": [
{"role":… See the full description on the dataset page: https://huggingface.co/datasets/llama-farm/arcnav-router-v1-dataset.digit-router-dataset
digit-router-dataset
34 709 Russian training rows for a two-step tool router over a catalogue of
95 headless utilities in 14 categories. Generated deterministically from the
catalogue's JSON schemas — no teacher model was used. 23.8 % of the rows are
refusals, and that fraction is the point of the dataset.
This is the set the published digitable-lol/digit-router-0.6b and
digitable-lol/digit-router-1.7b adapters were trained on.
1. Read this first: what this dataset… See the full description on the dataset page: https://huggingface.co/datasets/digitable-lol/digit-router-dataset.mikrotik-routeros-qa-dataset
MikroTik RouterOS Q&A Dataset
The first public structured Q&A dataset for MikroTik RouterOS fine-tuning. 1,672 instruction/response pairs grounded in the official MikroTik Confluence documentation, covering 215 distinct documentation pages.
Built to fine-tune zilalzihar/mikrotik-routeros-v01-GGUF, and released so others can train their own RouterOS-specialized models without re-doing the grounding work.
Files
File
Records
Purpose
qa-pairs.jsonl
1,672
Full… See the full description on the dataset page: https://huggingface.co/datasets/zilalzihar/mikrotik-routeros-qa-dataset.algocean-affect-router
algocean-affect-router
사용자 발화를 받아 지금 공감이 필요한지, 해결·정보가 필요한지 판정하도록 가르치는 LoRA SFT 데이터셋입니다.
사용자의 성격이 아니라 이 프롬프트가 지금 요구하는 응답 방식을 가르칩니다.
규모
파일
행 수
affect_router.jsonl
41,042
affect_router.eval.jsonl
2,000
형식: JSONL, messages 3턴
언어: 한국어 약 70% · 영어 약 30%
최소쌍(pair_id) 포함 — train/eval 분할 시 쌍 단위로 나눌 것
어디에 쓰나요
챗봇 응답 전 공감(F) vs 해결(T) 라우팅
같은 주제라도 어투에 따라 답이 달라져야 하는 경우
경량 모델로 톤 분기만 맡길 때
어떤 모델에 LoRA 하나요
출력이 짧고 클래스가 적어 가장 가벼운… See the full description on the dataset page: https://huggingface.co/datasets/Algocean/algocean-affect-router.router-v1
We make small models, you use small models — that’s it! Thanks for reading.
Router V1 Dataset
The Router V1 Dataset is a specialized resource designed to train and benchmark Large Language Model (LLM) routing and orchestration systems. It facilitates the development of intelligent dispatch mechanisms capable of analyzing an incoming user prompt and dynamically selecting the most optimal target model based on criteria such as efficacy and latancy.
Technical Overview… See the full description on the dataset page: https://huggingface.co/datasets/tensuai/router-v1.