sentence-transformers/multi-qa-mpnet-base-dot-v1
Sentence Similarity • 0.1B • Updated • 2.28M • • 193
Datasets:
Tasks:
Sentence Similarity
Modalities:
Text
Formats:
json
Sub-tasks:
semantic-similarity-classification
Languages:
English
Size:
1M - 10M
License:
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Dataset Card for "Amazon-QA"
Dataset Summary
This dataset contains Question and Answer data from Amazon.
Disclaimer: The team releasing Amazon-QA did not upload the dataset to the Hub and did not write a dataset card. These steps were done by the Hugging Face team.
Supported Tasks
- Sentence Transformers training; useful for semantic search and sentence similarity.
Languages
- English.
Dataset Structure
Each example in the dataset contains pairs of query and answer sentences and is formatted as a dictionary:
{"query": [sentence_1], "pos": [sentence_2]}
{"query": [sentence_1], "pos": [sentence_2]}
...
{"query": [sentence_1], "pos": [sentence_2]}
This dataset is useful for training Sentence Transformers models. Refer to the following post on how to train models using similar sentences.
Usage Example
Install the 🤗 Datasets library with pip install datasets and load the dataset from the Hub with:
from datasets import load_dataset
dataset = load_dataset("embedding-data/Amazon-QA")
The dataset is loaded as a DatasetDict and has the format:
DatasetDict({
train: Dataset({
features: ['query', 'pos'],
num_rows: 1095290
})
})
Review an example i with:
dataset["train"][0]
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