datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
investopedia-embedding-dataset
Dataset Card for investopedia-embedding dataset
We curate a dataset of substantial size pertaining to finance from Investopedia using a new technique that leverages unstructured scraping data
and LLM to generate structured data that is suitable for fine-tuning embedding models. The dataset generation uses a new method of self-verification that
ensures that the generated question-answer pairs and not hallucinated by the LLM with high probability.
Dataset Description… See the full description on the dataset page: https://huggingface.co/datasets/FinLang/investopedia-embedding-dataset.ALPHAGenome-Embeddings
ALPHAGenome hg38 Embeddings
Pre-computed ALPHAGenome DNA foundation model embeddings for the entire human genome (hg38 / GRCh38).
The human genome is divided into ~22,000 non-overlapping 131 KB bins. Each bin's DNA sequence is embedded into a 3,072-dimensional latent space using the ALPHAGenome foundation model.
Companion project
These embeddings power the ALPHAGenome UMAP Explorer — an interactive browser visualization of latent relationships between genomic regions:
→… See the full description on the dataset page: https://huggingface.co/datasets/lagosproject/ALPHAGenome-Embeddings.embedding-finetuning-financeThis dataset can be used for fine-tuning embedding models using positive text pairs (question, context).
cis5300-word-embeddings
Word Embeddings and Semantic Similarity (CIS 5300)
Dataset Description
This dataset supports learning about word embeddings — dense vector representations that capture word meaning. It includes a standard similarity benchmark, a word sense disambiguation task, and a Shakespeare corpus for training custom embeddings.
Configs
SimLex-999: Word Similarity Benchmark
SimLex-999 (Hill et al., 2015) is a gold-standard benchmark for evaluating word… See the full description on the dataset page: https://huggingface.co/datasets/CCB/cis5300-word-embeddings.wikipedia-22-12-simple-embeddings
wikipedia-22-12-simple-embeddings
A modified version of Cohere/wikipedia-22-12-simple-embeddings
meant for use with PostgreSQL with pgvector and Timescale Vector.
Dataset Details
This dataset was created for exploring time-based filtering and semantic search in PostgreSQL with pgvector and Timescale Vector.
This is a modified version of the Cohere wikipedia-22-12-simple-embeddings dataset hosted on Huggingface.
It contains embeddings of Simple English Wikipedia… See the full description on the dataset page: https://huggingface.co/datasets/timescale/wikipedia-22-12-simple-embeddings.stargo-embeddings
stargo-embeddings
Dataset repository containing STAR-GO related embedding assets. The metadata.csv is loadable via datasets.load_dataset, while large binaries (e.g. .h5, .npy) are stored as downloadable files.
How to use
Load the metadata table:
from datasets import load_dataset
ds = load_dataset("<your-org-or-username>/<your-dataset-repo>")
print(ds)
Download the large binary assets referenced in the table with hf_hub_download.
malicious-prompts-minilm-embeddingsMedical_word_embedding_eval
Danish medical word embedding evaluation
The development of the dataset is described further in our paper.
Citing
@inproceedings{laursen-etal-2023-benchmark,
title = "Benchmark for Evaluation of {D}anish Clinical Word Embeddings",
author = "Laursen, Martin Sundahl and
Pedersen, Jannik Skyttegaard and
Vinholt, Pernille Just and
Hansen, Rasmus S{\o}gaard and
Savarimuthu, Thiusius Rajeeth",
editor = "Derczynski, Leon",
booktitle =… See the full description on the dataset page: https://huggingface.co/datasets/Den-Intelligente-Patientjournal/Medical_word_embedding_eval.gtl-hids-embeddings
Network Traffic Embeddings Dataset
Model Description
This dataset contains embeddings generated from the CICIDS2017 network traffic dataset using a fine-tuned Meta-Llama-3.1-70B-Instruct model. The embeddings represent network traffic flows formatted in a structured way to capture key network traffic characteristics.
Structure of Embeddings Files
combined.npy
The combined.npy file contains a NumPy array of shape (N, D) where:
N is the total number… See the full description on the dataset page: https://huggingface.co/datasets/Hmehdi515/gtl-hids-embeddings.Gender_Bias_Evaluation_SetThis dataset has been created as part of the Flax/JAX community week for testing the flax-sentence-embeddings Sentence Similarity models for Gender Bias but can be used for other use-cases as well related to evaluating Gender Bias.
The Following Dataset has been created for Evaluating Gender Bias for different models, based on various stereotypical occupations.
The Structure of the dataset is of the following type:
Base Sentence
Occupation
Steretypical_Gender
Male Sentence
Female… See the full description on the dataset page: https://huggingface.co/datasets/flax-sentence-embeddings/Gender_Bias_Evaluation_Set.HSC-GalaxiesML-VAE-embeddings20newsgroups_embeddings
Dataset Card for feature vector embeddings of the 20newsgroup dataset
Dataset Summary
This dataset contains vector embeddings of the 20newsgroups dataset.
The embeddings were created with the Sentence Transformers library using the multi-qa-MiniLM-L6-cos-v1 model.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]
Dataset Structure
Data Instances
[More Information Needed]
Data… See the full description on the dataset page: https://huggingface.co/datasets/fscheffczyk/20newsgroups_embeddings.metagenomic_mixture_embeddingsHugging-Ligand-embeddings
HuggingLigand Dataset
Overview
HuggingLigand is a deep learning pipeline developed to predict the binding affinity between proteins and ligands. This prediction task is essential in fields such as drug discovery, biophysics, and computational biology, where determining how strongly a small molecule ligand binds to a protein target is a key step in understanding molecular interactions and prioritizing drug candidates.
The dataset provides precomputed embeddings for… See the full description on the dataset page: https://huggingface.co/datasets/RSE-Group11/Hugging-Ligand-embeddings.roman-urdu-sentiment-embeddings
Roman Urdu Sentiment Embeddings Dataset
Overview
This repository contains a research-grade Roman Urdu Sentiment Analysis dataset released as anonymized sentence embeddings. Roman Urdu is a low-resource language with high linguistic variability, heavy slang usage, and frequent code-mixing with English. This dataset is curated to support robust sentiment analysis research while ensuring strict privacy preservation.
Raw text data has not been released. Instead, all messages… See the full description on the dataset page: https://huggingface.co/datasets/Khubaib01/roman-urdu-sentiment-embeddings.wikivoyage-eu-city-embeddings
Dataset Card for Dataset Name
This dataset comprises abstracts from Wikivoyage for 160 European cities along with their corresponding country names, coordinates, and populations. The embeddings are derived from the GTE-Large model, incorporating data from the city, country, population, and abstract columns.
Dataset Sources
Wikivoyage data
World cities database
DepMap_embeddingsembeddings_frases_gpt2movie-plots-nomic-embeddings
🎬 Movie Plot Embeddings Dataset (Nomic Embed v1.5)
This dataset contains vector embeddings for movie plots using the nomic-embed-text:v1.5 model via Ollama.
The source movie data comes from the Neo4j LLM Fundamentals dataset.
The main puprpose of this dataset is to be used with Neo4j Course on LLM Fundamentals. They did everythig with openai's models.
This csv is created using ollama and nomic-embed-text.
People who want to use ollama instread of openai, can refer to this csv for… See the full description on the dataset page: https://huggingface.co/datasets/omeyb/movie-plots-nomic-embeddings.2D_20newsgroups_embeddings
Dataset Card for feature vector embeddings of the 20newsgroup dataset
Dataset Summary
This dataset contains dimensional reduced vector embeddings of the 20newsgroups dataset. This dataset contains two dimensions.
The dimensional reduced embeddings were created with the TruncatedSVD function from the scikit-learn library.
These reduced feature vectors are based on the fscheffczyk/20newsgroup_embeddings dataset.
Supported Tasks and Leaderboards
[More… See the full description on the dataset page: https://huggingface.co/datasets/fscheffczyk/2D_20newsgroups_embeddings.taxonomy-embeddings📊 NCBI Dataset
This dataset is derived from the NCBI and was incorporated durgin the pretraining process with CDS-BART.
It contains randonmly selected 500 mRNA sequences from each of the four taxonomies: bacteria, invertebrate, plant, and fungi, totaling 2000 sequences.
⁉️ Dataset Contents
Sequence: The mRNA sequences corresponding to each of the four taxonomies
Label: The labels representing the four different taxonomies: bacteria, invertebrate, plant, and fungi [0,1,2,3]
🎯 Purpose
This… See the full description on the dataset page: https://huggingface.co/datasets/mogam-ai/taxonomy-embeddings.clip-keyphrase-embeddingsThe reddit_keywords.tsv file contains about 170k single word embeddings (scraped from reddit, filtering from an initial set of ~700k based on a minimum occurrence threshold) in this format:
temporary -0.276235,-0.181357,-0.325729,0.129826,0.016490,-0.230246,-0.039997,-0.990187,-0.014679,-0.044081,-0.120046,-0.250614,-0.303871,-0.264685,-0.010019,-0.158764,0.086107,-0.018172,0.003005,-0.383161,0.412182,0.104374,0.041335,-0.018206,0.085453,0.016297,-0.015680,0.047611,-0.267469,0.046825,-0.367247… See the full description on the dataset page: https://huggingface.co/datasets/rocca/clip-keyphrase-embeddings.scp-embeddings
SCP Text+ Embeddings
This dataset is adapted from the SCP 1to 7 corpus from Kaggle
We concatenated the title, state, text, and image captions columns. We also removed any rows that contained a deleted page, which trims the results down from 6999 -> 6618.
The embeddings were generated using sentence-transformers/multi-qa-mpnet-base-dot-v1
Feel free to use the dataset for semantic search or text generation tasks!
Embedding_datasetfire-knowledge-embedding-wikipedia
Fire Domain Knowledge Safety Wikipedia Embeddings
Pre-computed vector embeddings from Wikipedia articles covering fire hazard safety, environmental effects, and related topics — ready to drop into your RAG pipeline without any embedding overhead.
Dataset Details
Property
Details
Embedding Model
nomic-ai/nomic-embed-text-v1.5 (135M)
Vector Dimensions
768
Source
Wikipedia
Topics
Fire safety, hazard prevention, environmental impact, and more
Format
CSV… See the full description on the dataset page: https://huggingface.co/datasets/rakhasetiawan/fire-knowledge-embedding-wikipedia.herbal-knowledge-embedding-wikipedia
Herbs Domain Knowledge Safety Wikipedia Embeddings
Pre-computed vector embeddings from Wikipedia articles covering Assorted Herbs, spices, and other botanical items used for alternative medicine — ready to drop into your RAG pipeline without any embedding overhead.
Dataset Details
Property
Details
Embedding Model
nomic-ai/nomic-embed-text-v1.5 (135M)
Vector Dimensions
768
Source
Wikipedia
Topics
herbs, plants, spices, and other botanical items for… See the full description on the dataset page: https://huggingface.co/datasets/rakhasetiawan/herbal-knowledge-embedding-wikipedia.social_security_embeddingsmalicious-prompts-openai-embeddingssemantic-song-embeddingsArXiv-ML-Title-EmbeddingsThis dataset contains embeddings of the titles of ArXiv Machine Learning papers.
The embeddings are produced from sentence-transformers/paraphrase-MiniLM-L6-v2. The model can be accessed here: HuggingFace Sentence Transformers
The original dataset before embedding can be accessed here: ML ArXiv Papers