datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Wikidata_Vectors_0.2
Wikidata Entity Embeddings 0.2
Dataset Summary
Wikidata Entity Embeddings is a dataset of embedding vectors for Wikidata entities. Each vector represents a Wikidata item (Q...) or property (P...) based on textual information extracted from Wikidata.
The dataset is part of the Wikidata Embedding Project, an initiative led by Wikimedia Deutschland in collaboration with Jina AI and IBM DataStax. The project provides a publicly accessible Wikidata Vector Database to… See the full description on the dataset page: https://huggingface.co/datasets/philippesaade/Wikidata_Vectors_0.2.v32-vectorsopeniti-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.rss_vectorsshamela-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.assistant-axis-vectors
Assistant Axis Vectors for gemma-3-27b-it
This dataset contains pre-computed role vectors and the assistant axis for gemma-3-27b-it.
Overview
These vectors were computed using the methodology from the paper "The Assistant Axis"
by Christina Lu et al. The vectors can be used for activation steering to control model behavior along the
"assistant-like" to "role-playing" spectrum.
Contents
gemma-3-27b-it/assistant_axis.pt - The computed assistant axis (principal… See the full description on the dataset page: https://huggingface.co/datasets/massines3a/assistant-axis-vectors.newsdataio_vectorsx86-instruction-test-vectors
x86-64 Instruction Test Vectors
Ground truth behavior of individual x86-64 instructions, captured by executing every encoding on real hardware and recording the resulting register and flag state. This is measured silicon behavior, not a model and not an emulator, so it also reflects implementation specific results such as the values an instruction leaves in flags that the architecture documents as undefined.
How it was generated
Each test case is produced by the… See the full description on the dataset page: https://huggingface.co/datasets/BinPrey/x86-instruction-test-vectors.googlenews_vectorsmusic-ocr-vectors
🎵 Music-OCR-Vectors
A comprehensive dataset of hand-drawn music scores paired with their digital vector and text representations.
📖 About the Dataset
Music-OCR-Vectors is a freely available, open-source dataset designed for Optical Music Recognition (OMR), machine learning, and computer vision research. It provides a bridge between handwritten musical notation and machine-readable formats.
For every hand-drawn music sheet in the dataset, the following ground-truth… See the full description on the dataset page: https://huggingface.co/datasets/Dddixyy/music-ocr-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.microduck-policy-golden-vectors
Microduck policy golden vectors
Observation → action pairs recorded from Pollen Robotics' trained
Microduck policies, so that anybody writing their
own runner can check it against the same numbers instead of against a video.
This is a conformance fixture, not a model and not a dataset to train on. It contains no
weights. If you want the networks, they are Pollen's, in
pollen-robotics/microduck and
pollen-robotics/microduck_rl.
What is in it
golden_policies.json… See the full description on the dataset page: https://huggingface.co/datasets/craigm26/microduck-policy-golden-vectors.zolai-knowledge-vectors
Zolai Knowledge Vectors
Pre-computed sentence embeddings for the Zolai-AI RAG Knowledge Brain -- a bilingual English-Zo (Tedim Chin) language preservation and learning system.
517,917 vectors from four knowledge sources, embedded with sentence-transformers/all-MiniLM-L6-v2 (384-dim).
What is Zolai?
Zolai (Tedim Zolai, ZVS 2018 orthography) is a Tibeto-Burman language spoken by the Zomi/Chin people of Myanmar and Northeast India. This dataset supports the Zolai-AI… See the full description on the dataset page: https://huggingface.co/datasets/peterpausianlian/zolai-knowledge-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.character-vectorsvectors2vibes-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.mmbench-vectors
mmbench — retrieval VECTORS (e5-base-v2)
Embedding vectors for the mmbench personalized retrieval benchmark. Vectors only
(no FAISS indexes) — rebuild Flat/IVF/HNSW locally (CPU, fast).
Model: intfloat/e5-base-v2 · dim 768 · L2-normalized · metric inner product (cosine)
Prefixes: documents/dialogue turns embedded as passage: ...; queries as query: ...
dtype: float16
Layout
docs/docvecs.npy — (1,990,000, 768) shared document corpus; row i ↔ docs/docs_ids.json[i]… See the full description on the dataset page: https://huggingface.co/datasets/tkdrnjs0621/mmbench-vectors.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.glove-6b-200d-vectorsSynVecSQLvectorstore-mental_health
Vectorstore Dataset: Mental Health
Overview
This dataset contains pre-computed vector embeddings for the mental health domain, ready for use in Retrieval-Augmented Generation (RAG) applications, semantic search, and knowledge base systems. The embeddings are generated from high-quality source documents using state-of-the-art sentence transformers, making it easy to build production-ready RAG applications without the computational overhead of embedding generation.… See the full description on the dataset page: https://huggingface.co/datasets/meetara-lab/vectorstore-mental_health.synth-persona-vectors
Persona Vectors
Mean activation vectors extracted from synthetic persona prompts.
This card is generated from the parquet files currently uploaded to the Hub.
Counts exclude the baseline_assistant row.
Available Vectors
Model
Config
Variants
Question set
QA filter
google/gemma-2-9b-it
google__gemma-2-9b-it__answer_mean
biography: 100 personas, 50 QA/persona; templated: 1000 personas, 50 QA/persona
train_test_split(n_train=50)
all
google/gemma-3-27b-it… See the full description on the dataset page: https://huggingface.co/datasets/implicit-personalization/synth-persona-vectors.end2end_textclassification_with_vectors
Dataset Card for end2end_textclassification_with_vectors
This dataset has been created with Argilla.
As shown in the sections below, this dataset can be loaded into Argilla as explained in Load with Argilla, or used directly with the datasets library in Load with datasets.
Dataset Summary
This dataset contains:
A dataset configuration file conforming to the Argilla dataset format named argilla.yaml. This configuration file will be used to configure the dataset when… See the full description on the dataset page: https://huggingface.co/datasets/argilla/end2end_textclassification_with_vectors.vector-sft2vectorstore-women_health
Vectorstore Dataset: Women Health
Overview
This dataset contains pre-computed vector embeddings for the women health domain, ready for use in Retrieval-Augmented Generation (RAG) applications, semantic search, and knowledge base systems. The embeddings are generated from high-quality source documents using state-of-the-art sentence transformers, making it easy to build production-ready RAG applications without the computational overhead of embedding generation.… See the full description on the dataset page: https://huggingface.co/datasets/meetara-lab/vectorstore-women_health.quran-rag-vectorsvectorstore-accounting
Vectorstore Dataset: Accounting
Overview
This dataset contains pre-computed vector embeddings for the accounting domain, ready for use in Retrieval-Augmented Generation (RAG) applications, semantic search, and knowledge base systems. The embeddings are generated from high-quality source documents using state-of-the-art sentence transformers, making it easy to build production-ready RAG applications without the computational overhead of embedding generation.… See the full description on the dataset page: https://huggingface.co/datasets/meetara-lab/vectorstore-accounting.