datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
openiti-vectors
OpenITI Vector Database — maktabati.ai
🇬🇧 English
This dataset contains the fully vectorized OpenITI RELEASE 2025-1-9 collection of classical Islamic texts, prepared for semantic search (RAG).
Each entry represents a text chunk from one of 8,943 works in the OpenITI corpus, together with its embedding vector and complete metadata.
Statistics:
4,696,703 chunks
8,943 works (primary editions only, status=pri from OpenITI TSV)
approx. 470 Parquet files (approx.… See the full description on the dataset page: https://huggingface.co/datasets/Maktabati/openiti-vectors.shamela-vectors
🇬🇧 English
The largest open-source vector database of the complete al-Maktaba al-Shamela (المكتبة الشاملة) Islamic text corpus, prepared for semantic search and Retrieval-Augmented Generation (RAG). Includes the full Quran text (6,236 verses, Hafs 'an 'Asim).
Statistics:
11,482,164 chunks from 8,589 classical Islamic books
6,236 Quran verses (one verse = one chunk, included in total)
40 categories covering the full breadth of Islamic scholarship
Period: 1st century AH to 15th… See the full description on the dataset page: https://huggingface.co/datasets/Maktabati/shamela-vectors.shamela-vectors
🇬🇧 English
The largest open-source vector database of the complete al-Maktaba al-Shamela (المكتبة الشاملة) Islamic text corpus, prepared for semantic search and Retrieval-Augmented Generation (RAG). Includes the full Quran text (6,236 verses, Hafs 'an 'Asim).
Statistics:
11,482,164 chunks from 8,589 classical Islamic books
6,236 Quran verses (one verse = one chunk, included in total)
40 categories covering the full breadth of Islamic scholarship
Period: 1st century AH to 15th… See the full description on the dataset page: https://huggingface.co/datasets/Kandil7/shamela-vectors.wiki-image-vectorsVector embeddings of images on Wikipedia using google/siglip2-base-patch16-384
Here's an example of how to use this
# /// script
# requires-python = ">=3.11"
# dependencies = [
# "gradio",
# "torch",
# "transformers",
# "pyarrow",
# "numpy",
# "huggingface_hub",
# ]
# ///
"""
Semantic search over Wikipedia/Commons image embeddings (SigLIP 2).
Run locally:
VECTORS=/path/to/vectors.parquet uv run app.py
Or let it pull from the Hub:
uv run app.py
"""
import… See the full description on the dataset page: https://huggingface.co/datasets/derenrich/wiki-image-vectors.Qwen3-0.6B-pts-steering-vectors
PTS Steering Vectors Dataset
A dataset of activation-based steering vectors created using the Pivotal Token Search (PTS) technique.
Details
Source: Generated using the PTS tool
Model: Qwen/Qwen3-0.6B
Dataset Structure
This dataset contains:
steering_vectors.jsonl: The main file with token-level steering vectors
Usage
These steering vectors can be used for activation-based steering during inference to guide language models toward particular… See the full description on the dataset page: https://huggingface.co/datasets/codelion/Qwen3-0.6B-pts-steering-vectors.vectors2vibes-discogs-metadata
Vectors2Vibes Discogs Metadata
Metadata for 24.6k tracks derived from Discogs Data and MTG Discogs-VI-YT. No audio files.
Note that earliest release year data is derived from MusicBrainz, as Discogs release year data is sparse and often unreliable.
Quick Facts:This dataset contains 24,689 tracks (release dates spanning from 1890-2026).
The top 5 represented decades are: 1960s (19.39%), 1970s (15.09%), 1980s (14.81%), 1950s (14.96%), and 1990s (14.27%).
The top 5 represented genres… See the full description on the dataset page: https://huggingface.co/datasets/vectors2vibes/vectors2vibes-discogs-metadata.echo-review-vectors
echo-review-vectors
Precomputed embeddings for the 45,864 distinct review texts in
Echo, encoded with
aynaval2003/echo-sbert-domain.
file
what it is
sbert-domain.fp16.npy
(45864, 768) float16, L2-normalised, row i matches row i of the parquet
corpus.parquet
row_index, content, n_rows, review_ids
45,864 vectors cover 64,280 review rows, because identical texts share one vector.
corpus.parquet is what joins a vector back to its reviews — without it the .npy
is an… See the full description on the dataset page: https://huggingface.co/datasets/aynaval2003/echo-review-vectors.qsd-eval-vectorsopen-web-vectors-manifest
Open Web Vector Initiative — Site Manifest
Per-site metadata for every site in the Open Web Vector Initiative, including
what each site told us about AI use on the day we asked.
The initiative — how the permission gate works, and what we will and will
not publish: https://divinci.ai/open-web-vectors/
The live directory — search the corpus, chat with any site in it, or claim
your own: https://divinci.ai/www-rag/
This dataset contains no page text and no embeddings. That is… See the full description on the dataset page: https://huggingface.co/datasets/Divinci-AI/open-web-vectors-manifest.vector-sft2quran-rag-vectorsrecipes_for_dishes_and_food_with_vectors_sentiment_ners
Description in English:
The dataset is collected from Russian-language Telegram channels with various food recipes,The dataset was collected and tagged automatically using the data collection and tagging service Scoutie.Try Scoutie and collect the same or another dataset using link for FREE.
Dataset fields:
taskId - task identifier in the Scouti service. text - main text. url - link to the publication. sourceLink - link to Telegram. subSourceLink - link to the… See the full description on the dataset page: https://huggingface.co/datasets/ScoutieAutoML/recipes_for_dishes_and_food_with_vectors_sentiment_ners.russian_jokes_with_vectors
Description in English:
The dataset is collected from Russian-language Telegram channels with jokes and anecdotes,The dataset was collected and tagged automatically using the data collection and tagging service Scoutie.Try Scoutie and collect the same or another dataset using link for FREE.
Dataset fields:
taskId - task identifier in the Scouti service. text - main text. url - link to the publication. sourceLink - link to Telegram. subSourceLink - link to the… See the full description on the dataset page: https://huggingface.co/datasets/ScoutieAutoML/russian_jokes_with_vectors.vector-sft3russian_events_vectors
Description in English:
The dataset is collected from Russian-language Telegram channels with information about various events and happenings in Russian regions,The dataset was collected and tagged automatically using the data collection and tagging service Scoutie.Try Scoutie and collect the same or another dataset using link for FREE.
Dataset fields:
taskId - task identifier in the Scouti service. text - main text. url - link to the publication. sourceLink -… See the full description on the dataset page: https://huggingface.co/datasets/ScoutieAutoML/russian_events_vectors.direction_vectors_ftq_enThese direction vectors of antonyms can be used to calculate fasttext interpretable embeddings on the fly, solving the OOV problem of other interpretable embeddings.
Simply calculate cosine similarity for each row.
19-4-embeddings28-3-26-both-emeddingsfull_core_ideas_vectorsalpaca-vectorsTPS_ESM3b_Vectorsexpressions-vectorsimprove_dataset_vectorsqwen3-safety-vectors
Qwen3 Safety Answer Trajectories
Dataset summary
Qwen3 Safety Answer Trajectories is a mechanistic-interpretability dataset containing generated answers, behavioral safety labels, and sampled hidden-state trajectories from three related Qwen3-4B checkpoints:
Dataset name
Model checkpoint
Role
qwen3_4b
Qwen/Qwen3-4B
Reference Qwen3 checkpoint
qwen3_4b_saferl
Qwen/Qwen3-4B-SafeRL
Official safety-tuned checkpoint
qwen3_4b_abliterated… See the full description on the dataset page: https://huggingface.co/datasets/DrExe/qwen3-safety-vectors.AI_HW3_detections_w_vectorssoccer-player-action-vectors
Soccer Player Action Vectors (based on Soccer Match Event Dataset)
Описание
Датасет содержит векторные представления футболистов,
построенные на основе событий матча из публичного датасета
Soccer Match Event Dataset.
Каждая строка соответствует одному игроку и агрегирует его игровые действия
(средние координаты, количество событий разных типов и т.п.).
Структура данных
Файл: player_vectors.csv
shortName — краткое имя игрока
action_count — общее количество… See the full description on the dataset page: https://huggingface.co/datasets/gosha222/soccer-player-action-vectors.trait-vectorsfull_bench_short_summaries_vectorsimprove_bench_ideas_vectorsexample_embedding_vectors