label int64 1 1 | text stringclasses 2
values | label_text stringclasses 1
value | embeddings listlengths 1.02k 1.02k |
|---|---|---|---|
1 | Stuning even for the non-gamer
This sound track was beautiful! It paints the senery in your mind so well I would recomend it even to people who hate vid. game music! I have played the game Chrono Cross but out of all of the games I have ever played it has the best music! It backs away from crude keyboarding and takes ... | positive | [
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0.011726243421435356,
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0.007417160551995039,
0.03882543742656708,
-0.... |
1 | The best soundtrack ever to anything.
I'm reading a lot of reviews saying that this is the best 'game soundtrack' and I figured that I'd write a review to disagree a bit. This in my opinino is Yasunori Mitsuda's ultimate masterpiece. The music is timeless and I'm been listening to it for years now and its beauty simpl... | positive | [
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-0.0803888812661171,
-0.004360740073025227,
0.06613318622112274,
-0.0070... |
amazon-polarity-qwen3-embeddings
This dataset contains pre-computed embeddings for the mteb/amazon_polarity dataset, generated using the Qwen/Qwen3-Embedding-0.6B model.
Embedding Generation Details
- Normalization: Embeddings are L2-normalized for cosine similarity
- Batch Size: 32
- Device: cpu
- Model Parameters: Default sentence-transformers encoding parameters
Model Information
The embeddings were generated using Qwen/Qwen3-Embedding-0.6B, a state-of-the-art embedding model. For more information about the model:
- Model Card: https://huggingface.co/Qwen/Qwen3-Embedding-0.6B
- Model Type: Sentence Transformer
- Framework: PyTorch + sentence-transformers
Citation
If you use this dataset, please cite both the original dataset and the embedding model:
Original Dataset
# See original dataset at https://huggingface.co/datasets/mteb/amazon_polarity
Embedding Model
# See model card at https://huggingface.co/Qwen/Qwen3-Embedding-0.6B
License
This dataset inherits the license from the original mteb/amazon_polarity dataset. Please refer to the original dataset for licensing information.
Generation Script
This dataset was generated using an automated pipeline. The embeddings can be reproduced using the sentence-transformers library with the Qwen/Qwen3-Embedding-0.6B model.
Contact
For questions or issues with this dataset, please open an issue in the repository.
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