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IMDb 50K — Qwen3 Embeddings
This dataset contains 50,000 IMDb movie reviews with precomputed 1,024-dimensional embeddings generated using Qwen3-Embedding-0.6B.
The dataset is shuffled and stored in Parquet format, with the original review text, embeddings, and binary sentiment labels preserved.
Dataset Structure
| Column | Description |
|---|---|
text |
Original IMDb review text |
embedding |
1,024-dimensional embedding vector |
label |
Sentiment label (0 = negative, 1 = positive) |
Purpose
The dataset provides ready-to-use embeddings for sentiment classification, clustering, dimensionality reduction, similarity analysis, and other machine learning experiments without needing to run the embedding model.
Attribution
Original dataset: IMDb Large Movie Review Dataset (Maas et al., 2011)
Embedding model: Qwen3-Embedding-0.6B
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