datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
LongBench-v2
LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks
🌐 Project Page: https://longbench2.github.io
💻 Github Repo: https://github.com/THUDM/LongBench
📚 Arxiv Paper: https://arxiv.org/abs/2412.15204
LongBench v2 is designed to assess the ability of LLMs to handle long-context problems requiring deep understanding and reasoning across real-world multitasks. LongBench v2 has the following features: (1) Length: Context length ranging from 8k to… See the full description on the dataset page: https://huggingface.co/datasets/zai-org/LongBench-v2.glaive-function-calling-v2English-Zomi-OPUS_Tatoeba_v20230412
English–Zomi Parallel Corpus (1.78M)
This dataset contains 1.78 million English–Zomi sentence pairs, created to support
machine translation, linguistic research, and large‑scale language model training.
It is fully open and permissively licensed for commercial and non‑commercial use.
🌐 Linguistic Background: Zomi, Tedim Chin, and ISO Codes
Zomi is the endonym (self‑chosen name) of the people and their language.However, Zomi does not yet have an official ISO 639‑3 code.… See the full description on the dataset page: https://huggingface.co/datasets/ZomiLearner/English-Zomi-OPUS_Tatoeba_v20230412.swallow-math-v2
SwallowMath-v2
Resources
📑 arXiv: Read our paper for detailed methodology at arXiv:2505.02881.
🤗 Sister Dataset: Discover SwallowCode2, our companion dataset for code generation.
🧮 What is it?
SwallowMath-v2 is a large-scale mathematical dataset containing 32 billion tokens, developed as the successor to SwallowMath-v1.
Building on the success of v1, this release aims to construct a larger-scale and more permissively licensed corpus to support open and… See the full description on the dataset page: https://huggingface.co/datasets/tokyotech-llm/swallow-math-v2.Nemotron-VLM-Dataset-v2
Nemotron-VLM-Dataset v2
Versions
Date
Commit
Changes
2025-11-05
head
Fix nights_cot dataset. Fix/filter broken <think> entries. Update fintabnet instructions. Update indexes.
2025-10-28
214051e
Initial Release
Dataset Description
Following up on Llama Nemotron VLM Dataset V1 with 3 million samples, we are releasing the Nemotron VLM Dataset V2 with almost three times as many high-quality samples.
This time, our focus was on three… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-VLM-Dataset-v2.swallow-code-v2
SwallowCode-v2
Resources
📑 arXiv: Read our paper for detailed methodology and results at arXiv:2505.02881.
🤗 Sister Dataset: Discover SwallowMath-v2, our companion dataset for mathematical reasoning.
💻 What is it?
SwallowCode-v1 was a high-quality Python code dataset generated through an LLM-based rewriting pipeline.
However, it had two significant limitations:
(1) it was distributed under the Llama 3.3 Community License, and
(2) its size was limited to… See the full description on the dataset page: https://huggingface.co/datasets/tokyotech-llm/swallow-code-v2.Nemotron-SFT-Science-v2
Dataset Description:
Nemotron-Science-v2 is a science reasoning dataset with synthetic (synthetic MCQ, RQA) and non-synthetic vendor problems and LLM-generated solutions. It comprises three domains (Physics, Biology, and Chemistry), two question formats (multiple-choice questions [MCQ] and open questions [OpenQ]), and three generation setups: chain-of-thought (CoT) reasoning without tools, Python tool usage, and search tools usage with the Tavily API.
The solutions were… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-SFT-Science-v2.MAPBench-V2For more details, please check our project page.
Paper: https://arxiv.org/abs/2601.05432
Repository: https://github.com/AMAP-ML/Thinking-with-Map
WizardLM_evol_instruct_V2_196k
News
🔥 🔥 🔥 [08/11/2023] We release WizardMath Models.
🔥 Our WizardMath-70B-V1.0 model slightly outperforms some closed-source LLMs on the GSM8K, including ChatGPT 3.5, Claude Instant 1 and PaLM 2 540B.
🔥 Our WizardMath-70B-V1.0 model achieves 81.6 pass@1 on the GSM8k Benchmarks, which is 24.8 points higher than the SOTA open-source LLM.
🔥 Our WizardMath-70B-V1.0 model achieves 22.7 pass@1 on the MATH Benchmarks, which is 9.2 points higher than the SOTA open-source LLM.… See the full description on the dataset page: https://huggingface.co/datasets/WizardLMTeam/WizardLM_evol_instruct_V2_196k.Cybersecurity-Dataset-Fenrir-v2.1
Cybersecurity Defense Instruction-Tuning Dataset (v2.1)
Created by Alican Kiraz
TL;DR
A ready-to-train dataset of 99,870 high-quality system / user / assistant triples for defensive, alignment-safe cybersecurity SFT training.
Apache-2.0 licensed and production-ready.
Scope: OWASP Top 10, MITRE ATT&CK, NIST CSF, CIS Controls, ASD Essential 8, modern authentication (OAuth 2 / OIDC / SAML), SSL / TLS, Cloud & DevSecOps, Cryptography, and AI Security.
1 What’s… See the full description on the dataset page: https://huggingface.co/datasets/AlicanKiraz0/Cybersecurity-Dataset-Fenrir-v2.1.osworld_v2_tasks
OSWorld V2 Task Classes
This gated dataset contains the official root-level task_*.py Python task classes for OSWorld V2.
The public GitHub repository keeps the task loader, helper utilities, and documentation. The task implementations are gated to reduce benchmark leakage and to help prevent evaluated agents from finding task answers, setup logic, or evaluator details online while executing a task.
Download from the public repository root with:
uvx --from huggingface_hub hf… See the full description on the dataset page: https://huggingface.co/datasets/xlangai/osworld_v2_tasks.spreadsheet-bench-v2-modified
SpreadsheetBench V2 Modified: Multi-Document QA
1,060 questions and reference answers grounded in 127 Excel workbooks, 35 PDFs and 9 DOCX files. This independent derivative of SpreadsheetBench 2 shifts the task from editing spreadsheets and producing workbook deliverables toward finding, interpreting and combining information in business documents.
An independent project built entirely from publicly available source material and newly authored QA annotations. No private company… See the full description on the dataset page: https://huggingface.co/datasets/hashmortar/spreadsheet-bench-v2-modified.V2Xverseglaive-function-calling-v2-sharegptThe glaive-function-calling-v2 dataset in sharegpt format.
You can use it in LLaMA Factory by specifying --dataset glaive_toolcall_100k.
Nemotron-SFT-Multilingual-v2
Dataset Description:
Nemotron-SFT-Multilingual-v2 is a multilingual supervised fine-tuning (SFT) dataset for post-training text-generation models. It is generated by translating seed data from Nemotron-Math-v2, Nemotron-Competitive-Programming-v1, and Nemotron-Science-v1, adding multilingual coverage for Hindi (hi), Korean (ko), Brazilian Portuguese (pt-br), and refreshed Japanese (ja) data.
The dataset is generated with a new data processing pipeline that avoids line-breaking… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-SFT-Multilingual-v2.glaive-function-calling-v2-llama-factory-convertThis is a converted dataset for https://huggingface.co/datasets/glaiveai/glaive-function-calling-v2 that allows sft in https://github.com/hiyouga/LLaMA-Factory for function calling fine tuning.
You need to add the following to the datasets.json file, and changed the file_name to your local path.
"glaive-function-calling-v2": {
"file_name": "./glaive-function-calling-v2/simple-function-calling-v2_converted.json",
"columns": {
"prompt": "instruction",
"query": "input"… See the full description on the dataset page: https://huggingface.co/datasets/Yhyu13/glaive-function-calling-v2-llama-factory-convert.quantized-llama-3.1-leaderboard-v2-evals
Open LLM Leaderboard v2 Benchmark Results
This artifact contains all the data from evaluations of Neural Magic's quantized Llama-3.1 models.
These evaluations were produced with lm-evaluation-harness by running the following command:
lm_eval \
--model vllm \
--model_args pretrained="<model_path>",dtype=auto,add_bos_token=False,max_model_len=4096,tensor_parallel_size="<num_gpus>",gpu_memory_utilization=0.8,enable_chunked_prefill=True \
--apply_chat_template \… See the full description on the dataset page: https://huggingface.co/datasets/neuralmagic/quantized-llama-3.1-leaderboard-v2-evals.nemotron-post-training-v2-qwen-3.5-9b-regen
Dataset Card for Nemotron Post Training v2 Qwen 3.5 9B Regen
Regenerated responses from nvidia/Nemotron-Post-Training-Dataset-v2 dataset using Qwen3.5 9B model.
Parameter
Value
Max Tokens
4096
Temperature
1.0
Top-k
20
Top-p
0.95
Repetition Penalty
1.5
Dataset consists only the english samples from the Nemotron Post Training Dataset. 85% of the chat prompts have reasoning enabled, every other category has reasoning disabled.
Category
Value
math… See the full description on the dataset page: https://huggingface.co/datasets/Dogacel/nemotron-post-training-v2-qwen-3.5-9b-regen.sn38-submission-r12-v2ade_corpus_v2_classification
ADE-Corpus-V2 Dataset: Adverse Drug Reaction Data.
This is a dataset for classification if a sentence is ADE-related (True) or not (False).
Train size: 17,637
Test size: 5,879
Source dataset
Paper
sn38-submission-r11-v2know_medical_dialogue_v2
Description:
The knowrohit07/know_medical_dialogues_v2 dataset is a collection of conversational exchanges between patients and doctors on various medical topics. It aims to capture the intricacies, uncertainties, and questions posed by individuals regarding their health and the medical guidance provided in response.
🎯 Intended Use:
This dataset is crafted for training Large Language Models (LLMs) with a focus on understanding and generating medically-informed dialogue.… See the full description on the dataset page: https://huggingface.co/datasets/knowrohit07/know_medical_dialogue_v2.nepali-law-v2
Nepali Source-Grounded Instruction Dataset
Synthetic Nepali instruction-tuning data generated with NVIDIA NeMo Data
Designer from authoritative Nepali documents (agriculture manuals, legal
texts). Answers are grounded strictly in the source; unanswerable questions
get an explicit refusal. Records use chat messages format plus metadata
and per-record quality_scores (grounding / correctness / naturalness, 1-5,
LLM-as-judge). One data/train-<shard>.jsonl per source document; shards… See the full description on the dataset page: https://huggingface.co/datasets/aarajbhattarai/nepali-law-v2.rejected-nepali-law-v2
Nepali Source-Grounded Instruction Dataset — REJECTED
Synthetic Nepali instruction-tuning data generated with NVIDIA NeMo Data
Designer from authoritative Nepali documents (agriculture manuals, legal
texts). Answers are grounded strictly in the source; unanswerable questions
get an explicit refusal. Records use chat messages format plus metadata
and per-record quality_scores (grounding / correctness / naturalness, 1-5,
LLM-as-judge). One data/train-<shard>.jsonl per source… See the full description on the dataset page: https://huggingface.co/datasets/aarajbhattarai/rejected-nepali-law-v2.flan_v2
Dataset Card for Flan V2
Dataset Summary
This is a processed version of the Flan V2 dataset.
I'm not affiliated with the creators, I'm just releasing the files in an easier-to-access format after processing.
The authors of the Flan Collection recommend experimenting with different mixing ratio's of tasks to get optimal results downstream.
Setup Instructions
Here are the steps I followed to get everything working:
Build AESLC and WinoGrande datasets… See the full description on the dataset page: https://huggingface.co/datasets/SirNeural/flan_v2.t3_data_V2LIMO-v2
LIMO: Less is More for Reasoning
Dataset for LIMO: Less is More for Reasoning
This is the updated version (v2) of the LIMO dataset, corresponding to the latest paper version as of July 30, 2025.
Usage
from datasets import load_dataset
# Load LIMO-v2 dataset
dataset = load_dataset("GAIR/LIMO-v2", split="train")
Previous Version
If you need the original LIMO dataset (corresponding to the initial paper version), you can access it at:
LIMO v1: GAIR/LIMO
# To… See the full description on the dataset page: https://huggingface.co/datasets/GAIR/LIMO-v2.glaive-function-calling-v2Modified version of the glaiveai/glaive-function-calling-v2 dataset
All samples in the glaive dataset is converted into the following format for better interoperability
[
{
"role":"system",
"content":"You are a helpful assistant with access to the functions.",
"functions":[
{
"name":"generate_password",
"description":"Generate a random password with specified criteria",
"parameters":{… See the full description on the dataset page: https://huggingface.co/datasets/Dulsara/glaive-function-calling-v2.c4tasky_v2Nemotron-VLM-Dataset-v2
Nemotron-VLM-Dataset v2
Versions
Date
Commit
Changes
2025-11-05
head
Fix nights_cot dataset. Fix/filter broken <think> entries. Update fintabnet instructions. Update indexes.
2025-10-28
214051e
Initial Release
Dataset Description
Following up on Llama Nemotron VLM Dataset V1 with 3 million samples, we are releasing the Nemotron VLM Dataset V2 with almost three times as many high-quality samples.
This time, our focus was on three main… See the full description on the dataset page: https://huggingface.co/datasets/introvoyz041/Nemotron-VLM-Dataset-v2.