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When should you replace a co2 cylinder in a inflateible pfd? | 0 | [
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When should you replace a co2 clynder in an inflatable pwd? | 0 | [
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When should you replace the co2 pfd? | 0 | [
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When should you replace the co2 cylinder in a pdf? | 0 | [
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] |
When should you replace the CO2 cylinder in a inflatable PFD? | 0 | [
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] |
When should you replace the co2 cilinder in an inflatable PFD? | 0 | [
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] |
When should you replace the co2 cylinder? | 0 | [
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] |
When should you replace the CO2 cylinder in an inflatable PFD? | 0 | [
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] |
When should you replace the CO2 container in an inflatable PFD? | 0 | [
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] |
When should you replace the co2 cylinder in an inflatable PFC? | 0 | [
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] |
When should you replace the CO2 cylinder in an inflateable PFD? | 0 | [
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] |
When should you replace the co2 cylinder in a inflateable pfd? | 0 | [
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] |
When to replace co2 in inflatable pfd? | 0 | [
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] |
When should you replace a CO2 cylinder in a inflatable PFD? | 0 | [
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] |
When should you replace the co2 cylinder on a pfd? | 0 | [
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] |
When do you replace a co2 cylinder on a pdf? | 0 | [
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] |
When should you replace the CO2 Cylinder in an inflatible PFD? | 0 | [
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Dataset Card for "wikianswers_embeddings_512"
Dataset Summary
nikhilchigali/wikianswers_embeddings_512 is a subset of the embedding-data/WikiAnswers (Link)
As opposed to the original dataset with 3,386,256 rows, this dataset contains only .13% of the total rows(sets). The sets of sentences have been unraveled into individual items with corresponding cluster IDs to identify sentences from the same set. Each Sentence has its associated cluster ID and embeddings of dimension 512.
Languages
English.
Dataset Structure
Each example in the dataset contains a sentence and its cluster id of other equivalent sentences. The sentences in the same cluster are paraphrases of each other. The embeddings for the dataset are created using the distiluse-base-multilingual-cased-v1 model.
{"sentence": [sentence], "cluster": [cluster_id], "embedding_512": [embeddings]}
{"sentence": [sentence], "cluster": [cluster_id], "embedding_512": [embeddings]}
{"sentence": [sentence], "cluster": [cluster_id], "embedding_512": [embeddings]}
...
{"sentence": [sentence], "cluster": [cluster_id], "embedding_512": [embeddings]}
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("nikhilchigali/wikianswers_embeddings_512")
The dataset is loaded as a DatasetDict and has the format for N examples:
DatasetDict({
train: Dataset({
features: ['sentence', "cluster", "embedding_512"],
num_rows: N
})
})
Review an example i with:
dataset["train"][i]
Source Data
embedding-data/WikiAnswers on HuggingFace (Link)
Note: This dataset is for the owner's personal use and claims no rights whatsoever.
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