datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
airbnb_embeddings
Overview
This dataset consists of AirBnB listings with property descriptions, reviews, and other metadata.
It also contains text embeddings of the property descriptions as well as image embeddings of the listing image. The text embeddings were created using OpenAI's text-embedding-3-small model and the image embeddings using OpenAI's clip-vit-base-patch32 model available on Hugging Face.
The text embeddings have 1536 dimensions, while the image embeddings have 512 dimensions.… See the full description on the dataset page: https://huggingface.co/datasets/MongoDB/airbnb_embeddings.20newsgroups_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.financebench-voyage-finance-2-embeddings
FinanceBench (voyage-finance-2 embeddings)
Pre-computed embeddings for the FinanceBench corpus. Skips ~$5-15 of Voyage API cost and ~30 minutes of ingest time vs re-embedding from raw PDFs. Intended consumer: the RAG agent at Rishabhmannu/financebench-rag-agent (install: pip install financebench-rag-agent).
What's in the box (frozen)
Field
Value
Source corpus
FinanceBench (SEC filings: 10-K, 10-Q, 8-K, earnings releases)
Parser
pypdf (canonical)… See the full description on the dataset page: https://huggingface.co/datasets/cmpunkmannu/financebench-voyage-finance-2-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.mulesoft-documentation-embeddings
mulesoft-documentation-embeddings
MuleSoft Documentation Embeddings for RAG Applications
Dataset Information
Version: 1.0.0
Created: 2025-09-16T02:41:16.352809
Source: Vector Database
License: MIT
Language: en
Task Categories
question-answering, retrieval, knowledge-base
Dataset Statistics
SkillPilotDataSet_v11
Total Objects: 6430
Unique Properties: 13
Knowledge Sources: mulesoft, user_defined_docs
Average Content Length: 5079… See the full description on the dataset page: https://huggingface.co/datasets/BassemE/mulesoft-documentation-embeddings.embedding-models
Reference models for integration into HF for Legal 🤗
This dataset comprises a collection of models aimed at streamlining and partially automating the embedding process. Each model entry within this dataset includes essential information such as model identifiers, embedding configurations, and specific parameters, ensuring that users can seamlessly integrate these models into their workflows with minimal setup and maximum efficiency.
Dataset Structure
Field
Type… See the full description on the dataset page: https://huggingface.co/datasets/HFforLegal/embedding-models.airbnb_embeddings
Overview
This dataset consists of AirBnB listings with property descriptions, reviews, and other metadata.
It also contains text embeddings of the property descriptions as well as image embeddings of the listing image. The text embeddings were created using OpenAI's text-embedding-3-small model and the image embeddings using OpenAI's clip-vit-base-patch32 model available on Hugging Face.
The text embeddings have 1536 dimensions, while the image embeddings have 512 dimensions.… See the full description on the dataset page: https://huggingface.co/datasets/Maki-99/airbnb_embeddings.