datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Handwritten-Latex-Datasets
Dataset
This data set includes common handwritten formulas in junior high schools and high schools, and is labeled in Latex format. Can be used to train models that recognize common numbers, fractions, and sets.
Dataset source
Collected in various junior high schools and high schools, handwritten by students.
Usage
The label is stored at json folder and scanned hand-writted pictures are stored at pic folder.
Scan the qr code of the picture to get the index and… See the full description on the dataset page: https://huggingface.co/datasets/WindyVerse/Handwritten-Latex-Datasets.bnci-windows
EEG Dataset
This dataset was created using braindecode, a library for deep learning with EEG/MEG/ECoG signals.
Dataset Information
Number of recordings: 1
Number of channels: 26
Sampling frequency: 250.0 Hz
Data type: Windowed (from Epochs object)
Number of windows: 48
Total size: 0.04 MB
Storage format: zarr
Usage
To load this dataset:
from braindecode.datasets import BaseConcatDataset
# Load dataset from Hugging Face Hub
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/Kkuntal990/bnci-windows.reddit_finance_43_250k
reddit finance 43 250k
reddit_finance_43_250k is a collection of 250k post/comment pairs from 43 financial, investing and crypto subreddits. Post must have all been text, with a length of 250chars, and a positive score. Each subreddit is narrowed down to the 70th qunatile before being mergered with their top 3 comments and than the other subs. Further score based methods are used to select the top 250k post/comment pairs.
The code to recreate the dataset is here:… See the full description on the dataset page: https://huggingface.co/datasets/winddude/reddit_finance_43_250k.bnci-windows-test
EEG Dataset
This dataset was created using braindecode, a library for deep learning with EEG/MEG/ECoG signals.
Dataset Information
Number of recordings: 1
Number of channels: 26
Sampling frequency: 250.0 Hz
Data type: Windowed (from Epochs object)
Number of windows: 48
Total size: 0.04 MB
Storage format: zarr
Usage
To load this dataset:
from braindecode.datasets import BaseConcatDataset
# Load dataset from Hugging Face Hub
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/Kkuntal990/bnci-windows-test.steuerllm_pretraining_dataset
SteuerLLM Pretraining Dataset
Project page | Paper | GitHub
Pretraining Dataset for German Tax Law filtered from FineWeb. This dataset was used for the continual pretraining stage of SteuerLLM, a specialized large language model for German tax law analysis.
Dataset Description
The SteuerLLM pretraining dataset is a domain-specific subset filtered from large-scale web corpora. It focuses on identifying and extracting tax-related content from German web data to adapt… See the full description on the dataset page: https://huggingface.co/datasets/windprak/steuerllm_pretraining_dataset.nvfp4-mtp-survey
Do Qwen3.8-27B NVFP4 repos actually ship a working MTP draft head?
A static survey of every NVFP4 quantization of Qwen3.8-27B and its finetunes that I could find
on the Hugging Face Hub, last run on 2026-08-24 (Rev 4) with
nvfp4_mtp_audit.py. Raw output: results.json.
I ran this to check a claim I had made in public, and the claim did not survive. The correction
is the first section, because it is the most important result here.
Revision history — read this, it is… See the full description on the dataset page: https://huggingface.co/datasets/windowsxp811203/nvfp4-mtp-survey.dataclaw-windows
Coding Agent Conversation Logs
This is a performance art project. Anthropic built their models on the world's freely shared information, then introduced increasingly dystopian data policies to stop anyone else from doing the same with their data - pulling up the ladder behind them. DataClaw lets you throw the ladder back down. The dataset it produces is yours to share.
Exported with DataClaw.
Tag: dataclaw - Browse all DataClaw datasets
Stats
Metric
Value… See the full description on the dataset page: https://huggingface.co/datasets/woctordho/dataclaw-windows.SiliconBench
SiliconBench: Serving Benchmark Prompts
The 200 prompts behind the speed measurements in SiliconBench: Speed, Memory, and Fidelity for LLM Serving on Unified-Memory Desktops. The paper evaluates nine Apple Silicon serving engines on speed, memory, and output fidelity, with an NVIDIA DGX Spark reference track.
Paper | Project website | Code and results
Configs
Each prompt is one request to an OpenAI-compatible /v1/chat/completions endpoint. The harness replays a… See the full description on the dataset page: https://huggingface.co/datasets/windchimeran/SiliconBench.windows-rtx-4060ti-8gb-moe-offload-bench-2026-05
RTX 4060 Ti 8GB — Multi-Model Benchmark (2026-05)
practitioner benchmarks on consumer hardware (8GB VRAM, 32GB RAM). 10 models tested, covering MoE expert offload, hybrid SSM architectures, dense models, MLA, dense partial GPU offload, and the 1B speed ceiling. all runs on the same physical rig, same methodology.
current leaderboard (decode tok/s at sweet spot)
model
active params
GGUF size
sweet spot tok/s
quality (6 tests)
architecture
Llama 3.2 1B
1.24B
771… See the full description on the dataset page: https://huggingface.co/datasets/witcheer/windows-rtx-4060ti-8gb-moe-offload-bench-2026-05.cards-wind-qwen-chat
cards-wind-qwen-chat
Combined API + chat SFT training data for the CARDS (climate contrarianism)
and WIND (wind-energy opposition) classifiers. Each row is an OpenAI-style
messages record (system / user / assistant) with RECoT teacher reasoning
(<think> + YAML) as the assistant target.
Every text appears twice — once per variant — so a single fine-tune learns both
behaviors, selected at inference by the system prompt:
Variant
System prompt
Assistant output
API
slim… See the full description on the dataset page: https://huggingface.co/datasets/iRanadheer/cards-wind-qwen-chat.test-windows-refactored
EEG Dataset
This dataset was created using braindecode, a library for deep learning with EEG/MEG/ECoG signals.
Dataset Information
Number of recordings: 1
Number of channels: 26
Sampling frequency: 250.0 Hz
Data type: Windowed (from Epochs object)
Number of windows: 48
Total size: 0.04 MB
Storage format: zarr
Usage
To load this dataset:
from braindecode.datasets import BaseConcatDataset
# Load dataset from Hugging Face Hub
dataset =… See the full description on the dataset page: https://huggingface.co/datasets/Kkuntal990/test-windows-refactored.wikifacts-window_2_v0linux_window_priv_esic_dataset
Linux & Windows Privilege Escalation Dataset
A structured dataset of known privilege escalation techniques for both Linux and Windows systems. Each entry includes a command, context, severity rating, mapped MITRE ATT&CK technique, and a reference link for further study.
This dataset is designed for use in:
Red team operations
LLM fine-tuning
Privilege escalation simulations
OSINT automation and enumeration tools
Cybersecurity education and training
📁 Dataset Format… See the full description on the dataset page: https://huggingface.co/datasets/darkknight25/linux_window_priv_esic_dataset.wikifacts-window_4_v0eis-text250
EIS-Text250: 1970s U.S. Environmental Impact Statements (text-only)
Per-page OCR/extraction text for 250 scanned 1970s U.S. federal
Environmental Impact Statements (EIS) from the Northwestern University
Library collection — the text-only companion to
Windsao/eis-subset50
(which carries full page images for a 50-doc subset). Built to test how current
models handle long, dense, historical government text: mean ~300 pages/doc,
1970s typewriter prose, OCR noise from degraded… See the full description on the dataset page: https://huggingface.co/datasets/Windsao/eis-text250.fineweb-webinstruct-matched_full_windowIHOP_CoT_zssn38-submissionwikifacts-window_6wikifacts-window_5_v0wind-edge-1.6-sft
Wind Lite SFT
Custom supervised fine-tuning dataset for Wind Lite 1.6 by North AI.
Dataset Summary
20,000 high-quality instruction-response pairs covering identity grounding, math reasoning, coding, general knowledge, and multi-turn conversations.
Data Composition
Category
Count
Description
Math & Reasoning
~7,000
Arithmetic, algebra, percentages, unit conversions — with step-by-step working
Coding
~4,000
Python, JavaScript, SQL, systems — with… See the full description on the dataset page: https://huggingface.co/datasets/North-ML1/wind-edge-1.6-sft.IHOPv01wikifacts-window_5Windows_Forensisc_artifactsaura-windows-pe-eval-v01
Traceix Mini Evaluation Dataset (Windows PE)
Traceix is a malware analysis platform that uses a neural network named AURA to classify files as safe or malicious. You can use Traceix at https://traceix.com.
This repository contains a mini evaluation dataset so that anyone can peer review AURA’s file-level classifications and recompute the basic metrics (accuracy, precision, recall, FPR, FNR) used in the Traceix model-quality page.
Each row includes:
sha256
true_label
predicted_label… See the full description on the dataset page: https://huggingface.co/datasets/PerkinsFund/aura-windows-pe-eval-v01.fineweb-webinstruct-matched-keyword-window-fullIHOP_flan_CoT
IHOP FLAN CoT ZeroShot
A recreation of the FLAN cot dataset for only zeroshot.
Because: the flan framework is nightmare to work with. And the "conceptofmind" repos are missing the raw targets for eval as well as incorrectly labeling "opt"
I also add double line breaks between every "thought"/"step" in the response, to make it easier to eval with something like PRM outlined in "Let’s Verify Step by Step"
The templates are very similar and close enough that it shold not matter.… See the full description on the dataset page: https://huggingface.co/datasets/winddude/IHOP_flan_CoT.business-model-kg-benchmark-outputs
Business Model KG Benchmark and Outputs
This repository contains the public evaluation package for Business Model KG:
gold benchmark triples and final generated graph outputs.
Business Model KG turns SEC 10-K business descriptions into standardized
business-model knowledge graphs. This package is meant for inspecting and
reproducing the evaluation side of the project without needing the full training
workspace or runtime model assets.
Layout
benchmarks/
dev/clean/… See the full description on the dataset page: https://huggingface.co/datasets/WindyITS/business-model-kg-benchmark-outputs.windows-rtx-4060ti-8gb-bench-2026-05
Local LLM Bench — RTX 4060 Ti 8GB
Real practitioner benchmarks of open-source LLMs on consumer 8GB VRAM hardware.
Hardware
GPU: NVIDIA GeForce RTX 4060 Ti (8GB VRAM)
CPU: AMD Ryzen 5 7600X (6 cores, AM5)
RAM: 32GB DDR5-6000 CL36
Platform: Windows 11
Runtime: LM Studio (CUDA backend)
Methodology
All models loaded with:
Quantization: Q4_K_M (GGUF)
Context length: 16384 tokens
GPU offload: maximum (full GPU residency where it fits)
Temperature: 0.7
Top-p: 0.9… See the full description on the dataset page: https://huggingface.co/datasets/witcheer/windows-rtx-4060ti-8gb-bench-2026-05.wikifacts-window_4