datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
comprehensive-arithmetic-problemscomprehensive-arithmetic-problems-carriesarithmeticA small battery of 10 tests that involve asking language models a simple arithmetic
problem in natural language.nanochat-climbmix-arithmetic-base10
nanochat ClimbMix + Base-10 Arithmetic
This dataset contains the first 170 shuffled ClimbMix training shards
used by nanochat's speedrun. The deterministic base-10 arithmetic corpus is
mixed into shards 00000..00149; the final
20 train shards are unchanged web-only padding.
The original validation shard (shard_06542.parquet) is also
copied unchanged.
Arithmetic corpus
Family
Examples
a + b = c (all ordered pairs 0..2000, two exposures)
8,008,002
a + b… See the full description on the dataset page: https://huggingface.co/datasets/Yujivus/nanochat-climbmix-arithmetic-base10.nanochat-climbmix-arithmetic-base7
nanochat ClimbMix + Arithmetic: base-7 numeral world
This is a deterministic base-7 rendering of
Yujivus/nanochat-climbmix-arithmetic-base10. It preserves
the exact shard names, row order, document order, arithmetic-document placement,
and non-numeric text of the source dataset.
Transformation rule
Every maximal ASCII digit run matching [0-9]+ is interpreted as a base-10
integer and rendered in base 7. Leading zeros are preserved as a prefix; signs,
punctuation… See the full description on the dataset page: https://huggingface.co/datasets/Yujivus/nanochat-climbmix-arithmetic-base7.qwen36-arithmetic-readouts
Arithmetic Intermediate Readout Sensitivity on Qwen3.6-27B
Arithmetic intermediate detection with a Jacobian lens depends sharply on the prompt token being read and the numeral forms accepted by the scorer. Across 105 order-of-operations items, the recorded hosted-lens responses contain the intermediate at rank 1 on 48 items at the trailing space, versus 4 at the preceding token. On the 25 held-out items with two-digit intermediates, rank-1 detection falls from 13 to 3 when… See the full description on the dataset page: https://huggingface.co/datasets/ec75hash/qwen36-arithmetic-readouts.simple-arithmetic-problemsArithmetic-Reasoning
SagheerLab/Arithmetic-Reasoning
A high-quality synthetic arithmetic and elementary mathematics reasoning dataset for training and evaluating small language models - not an "ultimate math" claim, but a clean, verified, tiered reasoning dataset where every answer is programmatically checked.
This dataset was built to train 100M-ish models that benefit disproportionately from clean, unambiguous examples. At 50M examples (45M train / 2.5M val / 2.5M test, ~5GB parquet) it is… See the full description on the dataset page: https://huggingface.co/datasets/SagheerLab/Arithmetic-Reasoning.nanochat-climbmix-arithmetic-base6
nanochat ClimbMix + Arithmetic: base-6 numeral world
This is a deterministic base-6 rendering of
Yujivus/nanochat-climbmix-arithmetic-base10. It preserves
the exact shard names, row order, document order, arithmetic-document placement,
and non-numeric text of the source dataset.
Transformation rule
Every maximal ASCII digit run matching [0-9]+ is interpreted as a base-10
integer and rendered in base 6. Leading zeros are preserved as a prefix; signs,
punctuation… See the full description on the dataset page: https://huggingface.co/datasets/Yujivus/nanochat-climbmix-arithmetic-base6.arithmetic_additionarithmetic_subtractionnanochat-calendar-arithmetic-base10
nanochat Base-10 Calendar Arithmetic
A deterministic, base-10 arithmetic corpus scoped to three cyclic calendar
units: hour-of-day (mod 24), day-of-week (mod 7), and
month-of-year (mod 12). Companion to
Yujivus/nanochat-climbmix-arithmetic-base10,
built the same way but scoped to real modular calendar units instead of
free-integer add/sub/mul/div/mod.
Every example is a single line — question and answer collapsed into one
equation, no exposed reasoning:
23:00 + 18965h = 04:00… See the full description on the dataset page: https://huggingface.co/datasets/liodon-ai/nanochat-calendar-arithmetic-base10.RWKV-7-ArithmeticRWKV-7-Arithmetic-0.1B 加减法运算模型的训练和测试数据集。
该模型实现基础加减法运算和加减法方程求解功能，能够处理整数部分为 1-12 位、小数部分为 0-6 位的数值，支持中英文数字、全半角格式以及大小写字符的多种表示形式，可实现基础加减法运算和加减法方程求解功能。
训练数据集说明
以下是我们使用的加减法训练数据类型，共包含 30000587 33000147 条单轮加减法 QA 数据，约 1B（1014434168） token。
数据文件名
数据条数
数据说明
示例
ADD_4M
3997733
1. 使用‘全角’、‘中文数字’、‘大写中文数字’随机替换整个数字2. 运算符附近有 1~2 个随机空格3. 含简单自然语言描述/自然语言噪声
{"text": "User: 249476576 减 796580834 还剩多少？\n\nAssistant: -547104258"}
ADD_2M
1999673
1. 使用‘全角’、‘中文数字’、‘大写中文数字’随机替换整个数字2. 运算符附近有 1~2… See the full description on the dataset page: https://huggingface.co/datasets/shoumenchougou/RWKV-7-Arithmetic.tram-arithmetic-responsessynthetic-dataset-1d-500K-50K-0.1-reverse-padzerodeepmind-math-arithmeticsynthetic-dataset-v2-3d-5M-500K-0.1-padzeromod-arithmetic
Modular Arithmetic Dataset
Synthetic dataset of modular-arithmetic problems of the form a mod b,
paired with the result and a hypothesis about the most suitable tokenizer.
Tokenizer hypothesis
For a mod b where b = 2^k × 5^j (no other prime factors), only the
rightmost max(k, j) digits of a determine the answer, because
10^max(k,j) ≡ 0 (mod b). A tokenizer that groups digits right-to-left
in chunks of that size exposes the relevant information as a single token.
For all… See the full description on the dataset page: https://huggingface.co/datasets/flexitok/mod-arithmetic.synthetic-dataset-v2-3d-3M-300K-0.1-reversetask087_new_operator_addsub_arithmetic
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task087_new_operator_addsub_arithmetic
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task087_new_operator_addsub_arithmetic.synthetic-dataset-v2-3d-5M-500K-0.1-reverse-padzerotask085_unnatural_addsub_arithmetic
Dataset Card for Natural Instructions (https://github.com/allenai/natural-instructions) Task: task085_unnatural_addsub_arithmetic
Additional Information
Citation Information
The following paper introduces the corpus in detail. If you use the corpus in published work, please cite it:
@misc{wang2022supernaturalinstructionsgeneralizationdeclarativeinstructions,
title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks}… See the full description on the dataset page: https://huggingface.co/datasets/Lots-of-LoRAs/task085_unnatural_addsub_arithmetic.synthetic-dataset-v2-3d-3M-300K-0.1-padzerosynthetic-dataset-1d-500K-50K-0.2-reversearithmetic-sorl-data
Arithmetic SoRL Data
Training and evaluation data for the SoRL Arithmetic Interpretability Study.
Small transformers trained on integer addition/subtraction, with
SoRL to externalize carry/borrow circuits
as explicit abstraction tokens.
Reference: Quirke et al., "Understanding Addition and Subtraction in Transformers" (2024).
Paper: arXiv:2402.02619 — see Table 8 for complexity classification and Section 3 for sub-task definitions.
Dataset Structure
Subfolder… See the full description on the dataset page: https://huggingface.co/datasets/thoughtworks/arithmetic-sorl-data.arithmetic_dataset
Arithmetic Puzzles Dataset
A collection of arithmetic puzzles with heavy use of variable assignment. Current LLMs struggle with variable indirection/multi-hop reasoning, this should be a tough test for them.
Inputs are a list of strings representing variable assignments (c=a+b), and the output is the integer answer.
Outputs are filtered to be between [-100, 100], and self-reference/looped dependencies are forbidden.
Splits are named like:
train_N 8k total examples of puzzles with N… See the full description on the dataset page: https://huggingface.co/datasets/neurallambda/arithmetic_dataset.synthetic-dataset-2d-1M-100K-0.2-reversesynthetic-dataset-3d-1M-100K-0.1-reversesynthetic-dataset-v2-3d-2M-200K-0.1-reverse-padzerosynthetic-dataset-3d-1M-100K-0.2-reverse-padzero