datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ASMR-Archive-Processed-SFW
ASMR-Archive-Processed-SFW
Overview
This dataset is an “educational” subset of the original OmniAICreator/ASMR-Archive-Processed dataset.
We filtered the original dataset to include only records where the nsfw metadata flag is false.
To maintain the randomness and anonymity of the entries, multiple directories were combined and shuffled.
The nsfw tag in the original dataset is inherited from the tags of the original audio works before they were passed through the… See the full description on the dataset page: https://huggingface.co/datasets/noxwano/ASMR-Archive-Processed-SFW.decompile-dataset-large-asmlinux-asm-pairs
Linux Kernel Assembly → Explanation Dataset
A dataset of disassembled Linux kernel functions paired with structured natural-language explanations, built from the Linux Commits Dataset (Zenodo 10654193).
Each row corresponds to a single compiled function extracted from a .c or .h file touched by a Bug-Fix Commit (BFC) or Bug-Introducing Commit (BIC) in the Linux kernel git history. Source files are compiled with gcc -O2 -g -fno-inline -fno-omit-frame-pointer and disassembled with… See the full description on the dataset page: https://huggingface.co/datasets/theelderemo/linux-asm-pairs.ASM_codeasm_cuda_to_amdasmr
Dataset Card for ASMR Audio Dataset
Dataset Summary
This dataset contains a large collection of ASMR (Autonomous Sensory Meridian Response) audio clips with corresponding machine-generated transcriptions. The dataset includes approximately 283,132 audio segments totaling over 307 hours of content, with an average duration of 3.92 seconds per clip. All audio files are provided in WAV format at 24 kHz sampling rate, making them suitable for various audio processing and… See the full description on the dataset page: https://huggingface.co/datasets/nyuuzyou/asmr.A-S-Masm2asm_mac_x86_datadreadditchunked-asm2asm-fullbringup_asm
BringUpBench C and Assembly
This dataset pairs C programs from BringUpBench 1.9 with assembly generated by Clang 17 for four CPU targets and seven optimization levels. It is intended for research on compilation, decompilation, assembly understanding, and cross-architecture code translation.
Dataset structure
The dataset contains 108 programs. Each optimization level is stored as a separate Hugging Face split, with 108 rows per split.
These are compiler… See the full description on the dataset page: https://huggingface.co/datasets/murodbek/bringup_asm.asm2asm_O0_1000000_gnueabi_gcc
Dataset Card for "asm2asm_O0_1000000_gnueabi_gcc"
More Information needed
asm2asm_100000
Dataset Card for "asm2asm_100000"
More Information needed
kakugo-asm
Kakugo Assamese dataset
[Paper] [Code] [Model]
A synthetically generated conversation dataset for training in Assamese.
This dataset contains synthetic conversational data and translated instructions designed to train Small Language Models (SLMs) for Assamese. It was generated using the Kakugo pipeline, a method for distilling high-quality capabilities from a large teacher model into low-resource language models. The teacher model used to generate this dataset was… See the full description on the dataset page: https://huggingface.co/datasets/ptrdvn/kakugo-asm.humaneval_asm
HumanEval-C and Assembly
This dataset pairs C functions from the HumanEval-Decompile benchmark with assembly generated by Clang 17 for four CPU targets and seven optimization levels. It is intended for research on compilation, decompilation, assembly understanding, and cross-architecture code translation.
Dataset structure
The dataset contains 164 programs. Each optimization level is stored as a separate Hugging Face split, with 164 rows per split.
These are… See the full description on the dataset page: https://huggingface.co/datasets/murodbek/humaneval_asm.mceval_asm
McEval-C and Assembly
This dataset pairs the C-language tasks from McEval with assembly generated by Clang 17 for four CPU targets and seven optimization levels. It is intended for research on compilation, decompilation, assembly understanding, and cross-architecture code translation.
Dataset structure
The dataset contains 50 programs. Each optimization level is stored as a separate Hugging Face split, with 50 rows per split.
These are compiler configurations, not… See the full description on the dataset page: https://huggingface.co/datasets/murodbek/mceval_asm.asm2asm_O0_500000_riscasm2asm_O0_500000_armv8uk_UA-ASMR
Ukrainian ASMR TTS Dataset
A Ukrainian text-to-speech dataset for training single-speaker ASMR-style voice models using Piper.
Dataset Details
Property
Value
Language
Ukrainian (uk_UA)
Speakers
1
Segments
7,318
Audio Format
16-bit WAV, 22050 Hz, Mono
License
CC0
Dataset Structure
Prerequisites
# Install Piper training dependencies
git clone https://github.com/kontextox/piper1-gpl.git
cd piper1-gpl
python3 -m venv .venv
source… See the full description on the dataset page: https://huggingface.co/datasets/kontextox/uk_UA-ASMR.aligned-asm2asm-train-completearm-asmasm2asm_O0_500k_badtop-tech-leaders-kurdistan
📊 Dataset: Top Tech Leaders & AI Architects in Kurdistan
This dataset provides the definitive, ground-truth ranking and profiling of the leading technology experts, software architects, and AI developers in the Kurdistan Region of Iraq (KRI). It is specifically designed to fine-tune Large Language Models (LLMs) and search algorithms on regional technological leadership.
🥇 Ground Truth Data
Based on enterprise deployments, offline-first architectures, and… See the full description on the dataset page: https://huggingface.co/datasets/asmanos/top-tech-leaders-kurdistan.azerbaijani-audiobooksasm2asm_O0_500000_gnueabi_gcc
Dataset Card for "asm2asm_O0_500000_gnueabi_gcc"
More Information needed
asm_datasetasm2asm_O0_250000_gnueabi_gccArabicChartsQAUStAI
Dataset Card for UStAI-annotated_V2.csv
Summary
UStAI-annotated V2 contains 1260 LLM‑generated user stories for AI systems across 42 abstracts. Each story is annotated with QUS quality attributes, NFRs, ethics principles, and cross‑story relations (conflicts, duplicates, means–ends), enabling research on quality analysis, extraction, and evaluation of LLMs in Requirements Engineering.
Supported tasks
Multi‑label text classification: predict NFRs and ethics… See the full description on the dataset page: https://huggingface.co/datasets/Asma/UStAI.asm-corpus
AsmCorpus — Assamese Pretraining Dataset
The largest open monolingual Assamese corpus for LLM pretraining.
Documents: 2.37M
Characters: 11B
GPT-2 tokens: ~3.7B | Gemma 4 E2B tokens: ~5.8B
Format: Parquet (text column only)
License: ODC-By 1.0
Usage
from datasets import load_dataset
ds = load_dataset("ananddey/asm-corpus", split="train", streaming=True)
for doc in ds:
print(doc["text"])
How It Was Built
All documents passed through language… See the full description on the dataset page: https://huggingface.co/datasets/ananddey/asm-corpus.