neon/test_runner/performance/pgvector

Source of the dataset for pgvector tests

This readme was copied from https://huggingface.co/datasets/Qdrant/dbpedia-entities-openai3-text-embedding-3-large-1536-1M

Download the parquet files

brew install git-lfs
git-lfs clone https://huggingface.co/datasets/Qdrant/dbpedia-entities-openai3-text-embedding-3-large-1536-1M

Load into postgres:

see loaddata.py in this directory

Rest of dataset card as on huggingface

---

dataset_info: features:

• name: _id dtype: string
• name: title dtype: string
• name: text dtype: string
• name: text-embedding-3-large-1536-embedding sequence: float64 splits:
• name: train num_bytes: 12679725776 num_examples: 1000000 download_size: 9551862565 dataset_size: 12679725776 configs:
• config_name: default data_files:
  • split: train path: data/train-* license: mit task_categories:
• feature-extraction language:
• en size_categories:
• 1M<n<10M

---

1M OpenAI Embeddings: text-embedding-3-large 1536 dimensions

• Created: February 2024.
• Text used for Embedding: title (string) + text (string)
• Embedding Model: OpenAI text-embedding-3-large
• This dataset was generated from the first 1M entries of https://huggingface.co/datasets/BeIR/dbpedia-entity, extracted by @KShivendu_