datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
DeepSeek-V4-Flash-0731-Teacher-Distillation-40513x
DeepSeek V4 Flash 0731 Teacher Distillation — 40,513 Retained Rows
Teacher-distillation corpus generated with
deepseek-ai/DeepSeek-V4-Flash-0731.
The original manifest contained 45,000 unique seeds.
Following generation, QC, retry-based repair, quarantine auditing,
and recovery adjudication, 40,513 rows were retained.
Composition
Bucket
Rows
Coding
5,601
Agentic
9,982
Cyber blue
13,000
Controlled cyber red
6,999
Tool use
4,931
Total
40,513… See the full description on the dataset page: https://huggingface.co/datasets/trjxter/DeepSeek-V4-Flash-0731-Teacher-Distillation-40513x.Gleipnir-Prefix-Teacher-Cache
Gleipnir Prefix Teacher Cache
Research artifact containing 133,947 intermediate tool-trajectory predictions
from Qwen/Qwen3.5-27B-FP8. This is a prediction cache, not a self-contained
trajectory dataset. It contains no trajectory text, original hard labels,
privileged rationales, or Kimi K3 full-trajectory targets.
Important numerical limitation
The completed cache failed its numerical-agreement audit. On a fixed
64-prefix sample, fresh versus cached probability… See the full description on the dataset page: https://huggingface.co/datasets/Jazhyc/Gleipnir-Prefix-Teacher-Cache.stage3-real-expansion-agent-teacher-separated-pilot
Teacher-Separated Expansion Agent Pilot
A 10-task inspection batch generated by Qwen3-235B-A22B-Instruct-2507 from real
CLAPNQ, PubMedQA, MAUD, ContractNLI, and FinQA source tasks.
The teacher-only trajectory-generation system prompt is recorded in
metadata/generation-manifest.json for auditability, but is absent from every
saved training trajectory. Each final messages list begins with the real
memory-wrapped task user message, followed by native assistant expand calls,
exact… See the full description on the dataset page: https://huggingface.co/datasets/leonli66/stage3-real-expansion-agent-teacher-separated-pilot.omegagenome-ntv3-teacher-cacheLeroyDyer___Spydaz_Web_AI_Top_Teacher_-details
Dataset Card for Evaluation run of LeroyDyer/Spydaz_Web_AI_Top_Teacher
Dataset automatically created during the evaluation run of model LeroyDyer/Spydaz_Web_AI_Top_Teacher
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always pointing to the latest… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/LeroyDyer___Spydaz_Web_AI_Top_Teacher_-details.LeroyDyer___Spydaz_Web_AI_AGI_R1_Math_Teacher-details
Dataset Card for Evaluation run of LeroyDyer/_Spydaz_Web_AI_AGI_R1_Math_Teacher
Dataset automatically created during the evaluation run of model LeroyDyer/_Spydaz_Web_AI_AGI_R1_Math_Teacher
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/LeroyDyer___Spydaz_Web_AI_AGI_R1_Math_Teacher-details.LeroyDyer___Spydaz_Web_AI_AGI_R1_Teacher_Coder-details
Dataset Card for Evaluation run of LeroyDyer/_Spydaz_Web_AI_AGI_R1_Teacher_Coder
Dataset automatically created during the evaluation run of model LeroyDyer/_Spydaz_Web_AI_AGI_R1_Teacher_Coder
The dataset is composed of 38 configuration(s), each one corresponding to one of the evaluated task.
The dataset has been created from 1 run(s). Each run can be found as a specific split in each configuration, the split being named using the timestamp of the run.The "train" split is always… See the full description on the dataset page: https://huggingface.co/datasets/open-llm-leaderboard/LeroyDyer___Spydaz_Web_AI_AGI_R1_Teacher_Coder-details.deepscaler-teacher-sft-vllm-official-40k-clean-v2
DeepScaleR Teacher40k Clean v2
Filtered version of ThunderstormXXL/deepscaler-teacher-sft-vllm-official-40k.
Filtering
minimum official reward: 1.0
maximum text tokens: 8192
maximum response chars: 65000
near-duplicate SimHash hamming threshold: 4
required <think>...</think> and final boxed answer after reasoning
exact text/problem/response dedupe and near problem dedupe
Counts
raw examples: 40300
kept examples: 21727
train examples: 21292
val… See the full description on the dataset page: https://huggingface.co/datasets/ThunderstormXXL/deepscaler-teacher-sft-vllm-official-40k-clean-v2.gsm8k-qwen3.5-teacher-traces
GSM8K Qwen3.5 Teacher Traces
This dataset contains teacher-model reasoning traces and final answers generated with DashScope qwen3.5-397b-a17b for the official GSM8K train split from openai/gsm8k.
It was created as a reusable public artifact for research on mathematical reasoning, text-level distillation, filtering, and teacher-data analysis. The original GSM8K questions come from openai/gsm8k; this dataset adds generated teacher outputs and filtering metadata.
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/jerryjsjsj/gsm8k-qwen3.5-teacher-traces.hanoi-crossing-aif-teacher
Hanoi Crossing AIF Teacher
25,000 unique prompt/completion examples generated by the observable GTSAM
active-inference controller on experiment/gtsam-aif-v2.
Each prompt contains only the acting player's visible poles and hand, legal
actions, remembered lift origin, and inferred opponent-state belief. It never
contains the referee's real opponent-private poles, hand, or private action.
The completion is one engine-legal action encoded as strict JSON.
Games cover N=1–4, both… See the full description on the dataset page: https://huggingface.co/datasets/anton96vice/hanoi-crossing-aif-teacher.sciworld-teacher32b-sft-partial
SciWorld — Qwen3-32B teacher trajectories for SFT (partial)
用 Qwen3-32B 在 ScienceWorld 训练集上跑完整轨迹, 导出成 SFT 数据。
这是一批不完整的采集: 目标 3592 条, 实际只成功 158 条。
⚠ 为什么不完整
采集脚本以 48 并发跑, 每条轨迹独占一个 ScienceWorld env(= 一个 JVM + py4j
socket)。默认 fd 上限 1024 被耗尽, 3434 条挂在 OSError(24, Too many open files)。
scripts/run_collect.sh 已修(加 ulimit -n 65536 与失败率闸门), 但这批数据是
修复前采的。当作抽样看, 不要当作完整训练集。
数据
messages + loss_mask 格式, 与 TCOD_examples/rose/rose_export_sft.py 对齐:
{"messages":… See the full description on the dataset page: https://huggingface.co/datasets/SeanWang0027/sciworld-teacher32b-sft-partial.deepscaler-teacher-sft-vllm-official-40k-clean-v3-no-reward-filter
deepscaler-teacher-sft-vllm-official-40k-clean-v3-no-reward-filter
Filtered version of ThunderstormXXL/deepscaler-teacher-sft-vllm-official-40k.
Filtering
reward filter enabled: False
minimum official reward: 1.0
scoring errors rejected: False
maximum text tokens: 8192
maximum response chars: 65000
near-duplicate SimHash hamming threshold: 4
required <think>...</think> and final boxed answer after reasoning
exact text/problem/response dedupe and near problem… See the full description on the dataset page: https://huggingface.co/datasets/ThunderstormXXL/deepscaler-teacher-sft-vllm-official-40k-clean-v3-no-reward-filter.deepscaler-teacher-sft-vllm-official-40k-clean-v4-conceptual
deepscaler-teacher-sft-vllm-official-40k-clean-v4-conceptual
Filtered version of ThunderstormXXL/deepscaler-teacher-sft-vllm-official-40k.
Filtering
reward filter enabled: False
minimum official reward: 1.0
scoring errors rejected: False
maximum text tokens: 32768
maximum response chars: 200000
near-duplicate SimHash hamming threshold: 4
required <think>...</think> and final boxed answer after reasoning
exact text/problem/response dedupe and near problem dedupe… See the full description on the dataset page: https://huggingface.co/datasets/ThunderstormXXL/deepscaler-teacher-sft-vllm-official-40k-clean-v4-conceptual.rhythm-env-teacher-trajectories
RhythmEnv teacher trajectories
Per-step (state, prompt, teacher_response, action, belief, reward) tuples
collected by replaying RhythmEnv with gpt-5.4 (Azure AI Foundry) as the
acting agent. Used as the SFT corpus for Algorithm Distillation.
Files
Each JSONL row is one step. Schema:
{
"seed": int, # episode seed (also determines hidden profile)
"step": int, # step index 0..27
"profile_name": str, # 'sampled_<seed>' for… See the full description on the dataset page: https://huggingface.co/datasets/InosLihka/rhythm-env-teacher-trajectories.teacher_hf_public
C++ Concolic Test Driver Generation Dataset
Dataset chứa 300 mẫu dùng để sinh/đánh giá test driver C++ bằng phương pháp concolic testing. Mỗi mẫu gồm mã nguồn hàm đích, prompt yêu cầu sinh test driver, và test driver đầu ra kèm kết quả coverage thực tế.
Thông tin tổng quan
Số mẫu: 300
Ngôn ngữ mã nguồn: C++
Repo nguồn: abseil (104 mẫu), bullet3 (196 mẫu)
Định dạng: JSONL (mỗi dòng là một JSON object)
Các trường dữ liệu
Trường
Kiểu
Mô tả… See the full description on the dataset page: https://huggingface.co/datasets/rd320uetvnu/teacher_hf_public.data-teacher-seallms-v2234
Data Teacher SeaLLMs v1
Bộ dữ liệu chưng cất tri thức pháp luật Việt Nam từ mô hình SeaLLMs-v1.
Dùng cho bài toán huấn luyện SLM trong dự án thạc sĩ.
minesweeper-teacher-kukurasu20k-qwen1.7b-e3-mask-rollouts-n2-tokens16384minesweeper-qwen3-4b-thinking-continued-by-teacher-kukurasu20k-qwen1.7b-e3-mask-t4096-r16384data-teacher-seallms-v3
Data Teacher SeaLLMs v1
Bộ dữ liệu chưng cất tri thức pháp luật Việt Nam từ mô hình SeaLLMs-v1.
Dùng cho bài toán huấn luyện SLM trong dự án thạc sĩ.
minesweeper-qwen3-4b-thinking-continued-by-teacher-kukurasu20k-nemotron-e3-mask-t4096-r16384minesweeper-teacher-kukurasu20k-nemotron-e3-mask-rollouts-n2-tokens16384