datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
cn-k12dyck-k128-seq_len_2048-1B
dyck-k128-seq_len_2048-1B
Procedurally generated k-shuffle Dyck bracket sequences (Hu et al. 2025, arXiv:2502.19249), as flat uint16 token-id .bin files. Token ids are 0-based: opening bracket type i is id i and its matching close is i + k, so ids span [0, 2k) and the vocabulary is 2k = 256.
Grammar parameters
param
value
k (bracket types)
128
max_depth
16
p_open
0.5
seq_length
2048
file
split
tokens
train.bin
train
999,999,488
val.bin
val
10,000… See the full description on the dataset page: https://huggingface.co/datasets/alexkstern/dyck-k128-seq_len_2048-1B.K12-Dataset
K12-KGraph
K12-KGraph is a curriculum-aligned knowledge graph built from official People's Education Press (PEP) K-12 textbooks. It focuses on curriculum cognition, namely the structured understanding of how school knowledge is organized, connected, and sequenced.
The current release covers mathematics, physics, chemistry, and biology across primary, middle, and high school, and includes three resources derived from the same graph:
K12-KGraph: the core knowledge graph
K12-Bench: a… See the full description on the dataset page: https://huggingface.co/datasets/tunaaa126/K12-Dataset.k12-standards-instruction-tasks
K-12 Curriculum Tasks (generated)
2,489 generated instruction/input/output records covering five curriculum tasks:
assessment creation, learning objective generation, misconception detection, standard
explanation, and standards Q&A. Content is predominantly mathematics.
Important: the name is misleading
Despite the name, this dataset contains no school directory data. There are four
columns - task, input, output, metadata - and no staff, principal, or school… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/k12-standards-instruction-tasks.k12-indian-curriculum-4.9m
BharatLLM K-12 Indian Curriculum Dataset (4.9M)
4,904,936 question-answer pairs covering CBSE/NCERT K-12 curriculum across 12 Indian languages.
Language
Script
Entries
English
Latin
~594K
Hindi
Devanagari
~449K
Bengali
Bengali
~408K
Telugu
Telugu
~408K
Tamil
Tamil
~408K
Kannada
Kannada
~408K
Malayalam
Malayalam
~408K
Marathi
Devanagari
~408K
Gujarati
Gujarati
~408K
Odia
Odia
~408K
PunjabiGurmukhi
~408K
Urdu
Nastaliq
~374K
Format
{… See the full description on the dataset page: https://huggingface.co/datasets/FoundryAILabs/k12-indian-curriculum-4.9m.k12-indian-curriculum-4.9m
BharatLLM K-12 Indian Curriculum Dataset (4.9M)
4,904,936 question-answer pairs covering CBSE/NCERT K-12 curriculum across 12 Indian languages.
Language
Script
Entries
English
Latin
~594K
Hindi
Devanagari
~449K
Bengali
Bengali
~408K
Telugu
Telugu
~408K
Tamil
Tamil
~408K
Kannada
Kannada
~408K
Malayalam
Malayalam
~408K
Marathi
Devanagari
~408K
Gujarati
Gujarati
~408K
Odia
Odia
~408K
Punjabi
Gurmukhi
~408K
Urdu
Nastaliq
~374K
Format… See the full description on the dataset page: https://huggingface.co/datasets/krittus/k12-indian-curriculum-4.9m.K12textbook覆盖小学、初中、高中的高质量中文K12教材语料，经过精细的文本抽取和数据处理，可用于学术研究
texas-k12-curriculum-standards-teks
Texas K-12 Curriculum Standards (TEKS-derived)
15,040 generated learning-objective records organized around the Texas Essential
Knowledge and Skills (TEKS) taxonomy, spanning core academic subjects, Career & Technical
Education clusters, and specialized program areas.
How this was built (read this first)
These records are programmatically generated, not transcribed from official standards
documents. A generator took a standards taxonomy - codes, grade levels… See the full description on the dataset page: https://huggingface.co/datasets/robworks-software/texas-k12-curriculum-standards-teks.cn_k12code_rose_initial_1_7B_SFT_10K_rollouts_Qwen3-4B-Thinking-2507_k12_t0.7_maxtok12288
code_rose_initial_1_7B_SFT_10K — rollouts (Qwen3-4B-Thinking-2507, k=12)
Pass@k completions generated with vLLM over the prefixes in
CL-From-Nothing/code_rose_initial_1_7B_SFT_10K.
Generation config
Model
Qwen3-4B-Thinking-2507
Samples per question (k)
12
Temperature
0.7
top_p
0.9
max_tokens
12288
max_model_len
32768
Questions
7250 (index 0–7249, full split)
Total rows
87000 (7250 × 12)
Generated by complete_prefix_vllm.py… See the full description on the dataset page: https://huggingface.co/datasets/CL-From-Nothing/code_rose_initial_1_7B_SFT_10K_rollouts_Qwen3-4B-Thinking-2507_k12_t0.7_maxtok12288.NMC-cn_k12-20k-r1_32b_distilled本数据集数据来源为NuminaMath-CoT数据集的cn_k12数据。我们从这里面提取了20000条问题，并使用DeepSeek-R1-Distill-Qwen-32B模型进行了回答。
distilled_s0_e20000.jsonl包含这个数据集的数据，下面介绍数据标签：
idx：索引号（0~19999）
question：原数据集中的problem标签，是一个可能包含多个子问题的数学问题字符串
gt_cot：愿数据集中的solution标签，是经过GPT-4o整理的答案字符串
pred_cot：根据question标签，模型DeepSeek-R1-Distill-Qwen-32B的回答字符串
pred_cot_token_len：pred_cot标签下的字符串转化成token之后的长度（不包含最前面的<think>\n部分，这个在生成的时候是在prompt里面，我后来加到这里了）
message：根据question标签和pred_cot标签，构造的问题-回答数据对
统计了一下平均回答token长度，为3169.4251
d-k12K12textbook覆盖小学、初中、高中的高质量中文K12教材语料，经过精细的文本抽取和数据处理，可用于学术研究