datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ExperimentDATA_knowledge_distillation_vs_fine_tuningRamanBench
RamanBench Dataset Mirror
⚠️ RESEARCH MIRROR ONLY — All datasets are provided for research/educational purposes. Original copyrights remain with original authors. See Sources & Licenses below.
A unified mirror of 87 Raman spectroscopy datasets from the RamanBench benchmark. Wide-format Parquet files for fast, reliable access.
Quick Start
from raman_bench import RamanBenchmark
# Fast mirror access (default)
bench = RamanBenchmark(… See the full description on the dataset page: https://huggingface.co/datasets/HTW-KI-Werkstatt/RamanBench.dojo_stock_kline
Languages: 简体中文 · English
dojo_stock_kline — Stock Daily Bars
Overview
Daily OHLCV history for US, CN, and HK equities, including cumulative adjustment factors and dividend/split flags.
Files
File
Description
data.parquet
Market-wide daily bars
Key Fields
Field
Description
symbol
Join key
kline_t
Bar interval; snapshots use "1D" for daily bars
bar_time
Bar timestamp (trade date)
open / high / low /… See the full description on the dataset page: https://huggingface.co/datasets/AlphaDojo/dojo_stock_kline.KodCode-V1-SFT-R1
🐱 KodCode: A Diverse, Challenging, and Verifiable Synthetic Dataset for Coding
KodCode is the largest fully-synthetic open-source dataset providing verifiable solutions and tests for coding tasks. It contains 12 distinct subsets spanning various domains (from algorithmic to package-specific knowledge) and difficulty levels (from basic coding exercises to interview and competitive programming challenges). KodCode is designed for both supervised fine-tuning (SFT) and RL tuning.
🕸️… See the full description on the dataset page: https://huggingface.co/datasets/KodCode/KodCode-V1-SFT-R1.dojo_forex_kline
Languages: 简体中文 · English
dojo_forex_kline — FX Daily Bars
Overview
Daily OHLC and amplitude for major currency pairs. Used to convert revenue, profit, and other filing amounts into a single currency when report currency and listing/analysis currency differ.
Typical case: regional revenue in HKD in dojo_main_income while analysis targets USD — apply HKDUSD (or equivalent) at the report date.
Intended Use: Cross-Currency Revenue Breakdown… See the full description on the dataset page: https://huggingface.co/datasets/AlphaDojo/dojo_forex_kline.KodCode-V1
🐱 KodCode: A Diverse, Challenging, and Verifiable Synthetic Dataset for Coding
KodCode is the largest fully-synthetic open-source dataset providing verifiable solutions and tests for coding tasks. It contains 12 distinct subsets spanning various domains (from algorithmic to package-specific knowledge) and difficulty levels (from basic coding exercises to interview and competitive programming challenges). KodCode is designed for both supervised fine-tuning (SFT) and RL tuning.
🕸️… See the full description on the dataset page: https://huggingface.co/datasets/KodCode/KodCode-V1.quasar-axrvi-v10ClimbLab-JaJapanese / 日本語版
ClimbLab-Ja
ClimbLab-Ja is a high-quality 300-billion-token Japanese corpus with 20 clusters. It is a Japanese adaptation of the nvidia/Nemotron-ClimbLab approach. Based on LLM-jp Corpus v4, we semantically reorganized and filtered the dataset into 20 distinct clusters, resulting in a high-quality 300-billion-token corpus. Specifically, we first grouped the data into 1,000 groups based on topic information. Then we assigned six scores from 0 to 5 to each group… See the full description on the dataset page: https://huggingface.co/datasets/KantaHayashiAI/ClimbLab-Ja.KMMLU
KMMLU (Korean-MMLU)
We propose KMMLU, a new Korean benchmark with 35,030 expert-level multiple-choice questions across 45 subjects ranging from humanities to STEM.
Unlike previous Korean benchmarks that are translated from existing English benchmarks, KMMLU is collected from original Korean exams, capturing linguistic and cultural aspects of the Korean language.
We test 26 publically available and proprietary LLMs, identifying significant room for improvement.
The best publicly… See the full description on the dataset page: https://huggingface.co/datasets/HAERAE-HUB/KMMLU.hit-asraitw-processed-labeled-full
AiTW Processed Full with App Labels
This repository contains a full processed Android in the Wild (AiTW) mirror together with an app-labeled step index, official split assignment by episode_id, major-app statistics, and a ready-to-train Gmail subset.
Why This Exists
AiTW is large and not easy to navigate by app. The original labels contain useful fields such as goal_info, current_activity, and action coordinates, but users often need extra processing before they… See the full description on the dataset page: https://huggingface.co/datasets/KMK040412/aitw-processed-labeled-full.epic-kitchens-100-clips
EPIC-KITCHENS-100 Extracted Clips
About
Dataset of 37455 video clips (24GB) extracted from videos in the EPIC-KITCHENS-100 dataset,
more precisely the extension part not contained in EPIC-KITCHENS-55. For details,
see https://www.lightly.ai/product-updates/epickitchens-100-in-lightlystudio.
The clips folder contains one video for every narration from action annotations stored
in {participant_id}/{narration_id}.mp4. The videos have been downscaled an compressed for easier… See the full description on the dataset page: https://huggingface.co/datasets/lightly-ai/epic-kitchens-100-clips.python-toolcallsLogs from run_python_code tool used for benchmarking.
multi_task_multi_modal_knowledge_retrieval_benchmark_M2KR
PreFLMR M2KR Dataset Card
Dataset details
Dataset type:
M2KR is a benchmark dataset for multimodal knowledge retrieval. It contains a collection of tasks and datasets for training and evaluating multimodal knowledge retrieval models.
We pre-process the datasets into a uniform format and write several task-specific prompting instructions for each dataset. The details of the instruction can be found in the paper. The M2KR benchmark contains three types of tasks:… See the full description on the dataset page: https://huggingface.co/datasets/BByrneLab/multi_task_multi_modal_knowledge_retrieval_benchmark_M2KR.seamless-align-enA-koA.speaker-embedding.w2vbert-600mblip3-kale
🥬 BLIP3-KALE:Knowledge Augmented Large-scale Dense Captions
BLIP3-KALE is an open-source dataset of 218 million image-text pairs, featuring knowledge-augmented dense captions combining web-scale knowledge with detailed image descriptions.
Paper: [To be added]
Uses
BLIP3-KALE is designed to facilitate research in multimodal pretraining. The dataset can be used for training large multimodal models that require factually grounded, dense image captions. It has already been an… See the full description on the dataset page: https://huggingface.co/datasets/Salesforce/blip3-kale.kernelbench-mega-traces
KernelBench-Mega agent traces
Coding agents writing full GPU megakernels across Blackwell / H100 / B200, scored as speedup over reference; contamination-audited (23 verified cells).
Each .jsonl file is one agent run in Claude-Code session format, viewable with the agent trace viewer. Filename = run id; manifest.csv maps each run to model / harness / problem / GPU / score.
23 agent traces · live leaderboard: https://kernelbench.com/mega
Secrets redacted. Full reasoning for… See the full description on the dataset page: https://huggingface.co/datasets/Infatoshi/kernelbench-mega-traces.fineweb-edu-gpt2klines-binance
Binance USDT OHLCV Klines (spot + perpetual futures)
Historical OHLCV candlestick (kline) data for Binance USDT markets — both
spot and USDT-margined perpetual futures — stored as zstd-compressed Parquet.
Coverage
spot
futures (USDT perp)
Pairs
~490
~791 (includes delisted — survivorship-bias-free)
Timeframes
1m · 3m · 5m · 15m · 1h · 4h · 1d
1m · 3m · 5m · 15m · 1h · 4h · 8h · 1d
History
2017-08 → 2025-05
2020-05 → 2026-07
Extras
—
sparse mark… See the full description on the dataset page: https://huggingface.co/datasets/rogerdehe/klines-binance.fasttAthar-Embeddingsklines-bybit
Bybit USDT Perpetual OHLCV Klines
Historical OHLCV candlestick (kline) data for Bybit USDT-margined perpetual
futures, stored as zstd-compressed Parquet. Includes delisted symbols, so it
is usable for point-in-time / survivorship-bias-free backtests.
⚠️ Under construction. This dataset is being actively built. Coarser
timeframes (15m · 1h · 4h · 1d) and 5m/3m are being uploaded first; 1m is
still downloading and will be added. Pair and timeframe coverage will grow.
A per-file… See the full description on the dataset page: https://huggingface.co/datasets/rogerdehe/klines-bybit.kimi-k3-distillation
kimi-k3-distillation
Single-teacher slice of
r0b0tlab/qwen3.8-max-glm5.2-kimi-k3-distillation,
filtered to teacher_model == "kimi-code/k3" only. The Qwen3.8-Max-Preview and
GLM-5.2 traces are removed.
4,347 rows — 3,918 train / 212 validation / 217 test.
from datasets import load_dataset
ds = load_dataset("beyoru/kimi-k3-distillation") # sft: messages + tools
ds = load_dataset("beyoru/kimi-k3-distillation", "canonical") # + full audit columns… See the full description on the dataset page: https://huggingface.co/datasets/beyoru/kimi-k3-distillation.qwen3.8-max-glm5.2-kimi-k3-distillation
Multi-Teacher Distillation Dataset (57,937 traces)
A quality-filtered, deduplicated, multi-teacher SFT corpus combining traces from three frontier models across math, code, reasoning, instruction-following, tool-use, science, long-context, multilingual, and creative dialogue domains.
Teachers
Teacher
Provider
Traces
Qwen3.8-Max-Preview
Alibaba Cloud Model Studio
48,283
GLM-5.2
Z.AI Coding Plan
5,307
Kimi Code K3
Moonshot AI (Kimi)
4,347… See the full description on the dataset page: https://huggingface.co/datasets/r0b0tlab/qwen3.8-max-glm5.2-kimi-k3-distillation.leetcode-problem-solutions
LeetCode Solution Dataset
This dataset contains community-contributed LeetCode solutions scraped from public discussions and solution pages, enriched with metadata such as vote counts, author info, tags, and full code content. The goal is to make high-quality, peer-reviewed coding solutions programmatically accessible for research, analysis, educational use, or developer tooling.
Column Descriptions
Column Name
Type
Description
question_slug
string
The unique… See the full description on the dataset page: https://huggingface.co/datasets/kaysss/leetcode-problem-solutions.coco-karpathy
Dataset Card for "yerevann/coco-karpathy"
The Karpathy split of COCO for image captioning.
kernelbench-hard-traces
KernelBench-Hard agent traces
Frontier coding agents writing optimized CUDA/Triton kernels (FP8 GEMM, paged
attention, MoE, W4A16, KDA, Top-k) on RTX PRO 6000 Blackwell, H100 PCIe, and
B200; roofline-graded.
Each .jsonl file is one agent run in Claude-Code session format, viewable with
the Hugging Face Agent Trace viewer (Data Studio → open a row). Filename =
run id.
Live leaderboard: https://kernelbench.com/hard
Secrets redacted. Full reasoning for open-provider routes… See the full description on the dataset page: https://huggingface.co/datasets/Infatoshi/kernelbench-hard-traces.kagg_anima_loratwaitch-txtKodCode-Light-RL-10K
🐱 KodCode: A Diverse, Challenging, and Verifiable Synthetic Dataset for Coding
KodCode is the largest fully-synthetic open-source dataset providing verifiable solutions and tests for coding tasks. It contains 12 distinct subsets spanning various domains (from algorithmic to package-specific knowledge) and difficulty levels (from basic coding exercises to interview and competitive programming challenges). KodCode is designed for both supervised fine-tuning (SFT) and RL tuning.
🕸️… See the full description on the dataset page: https://huggingface.co/datasets/KodCode/KodCode-Light-RL-10K.