README.md

metadata

license: mit
task_categories:
  - feature-extraction
  - text-classification
language:
  - en
tags:
  - news
  - embeddings
  - semantic-search
size_categories:
  - 100K<n<1M

News Embeddings Dataset

This dataset contains news article embeddings generated using the Qwen/Qwen3-Embedding-0.6B model.

Source

The original news articles were sourced from the Global News Dataset on Kaggle.

Dataset Structure

Each row contains:

• article_id: Unique identifier for the article from the source dataset
• text: Concatenation of title and description (separated by \n---\n)
• embedding: 1024-dimensional embedding vector

Embedding Model

• Model: Qwen/Qwen3-Embedding-0.6B
• Prompt: "Instruct: Given a news article summary, generate a semantic embedding that captures its key features and characteristics \nArticle:"

Usage

import polars as pl
from huggingface_hub import hf_hub_download

# Download the parquet file
path = hf_hub_download(repo_id="live-wire/news_embeddings", filename="embed.parquet", repo_type="dataset")
df = pl.read_parquet(path)