text
stringclasses 10
values | label
class label 5
classes |
|---|---|
I'm really happy with the purchase, but the price was a bit higher than I initially thought. | 2price
|
The website took too long to process my order, and I had to follow up multiple times to get an update on the status. However, the product itself is great and I'm happy with the quality. | 3order-processing
|
I was surprised by the quality of this product considering its price is relatively low. The features are on par with more expensive models I've seen, but it lacks some advanced functionality. | 5product-quality
|
The product arrived in a timely manner, but the packaging could have been better as it got crushed during transit. | 4product-delivery
|
The product was out of stock for months, but I finally managed to purchase it. It's not as popular as other items in the store, which might explain the availability issues. | 0product-availability
|
I'm extremely frustrated because the product I ordered is still not available for shipping despite being listed as in stock. The last update on the website says it will be restocked in a week. | 0product-availability
|
I'm extremely satisfied with the delivery of my new laptop, the shipping was super fast and the packaging was great. I received it in just 2 days after placing the order! | 4product-delivery
|
I'm not sure if this high-end smartphone is worth the hefty price tag, considering it's just slightly better than last year's model. | 5product-quality
|
The product I ordered arrived in just 2 days, which is impressive considering I live in a rural area. The packaging was well-protected and there were no signs of damage. | 4product-delivery
|
I'm really happy with this purchase, but I have to say that the price of this item is way too high for its quality. I paid almost $100 for something that could be found at a local store for half the price. | 5product-quality
|
Dataset Card for my-distiset-1e19c746
This dataset has been created with distilabel.
Dataset Summary
This dataset contains a pipeline.yaml which can be used to reproduce the pipeline that generated it in distilabel using the distilabel CLI:
distilabel pipeline run --config "https://huggingface.co/datasets/navinavi029/my-distiset-1e19c746/raw/main/pipeline.yaml"
or explore the configuration:
distilabel pipeline info --config "https://huggingface.co/datasets/navinavi029/my-distiset-1e19c746/raw/main/pipeline.yaml"
Dataset structure
The examples have the following structure per configuration:
Configuration: default
{
"label": 2,
"text": "I\u0027m really happy with the purchase, but the price was a bit higher than I initially thought."
}
This subset can be loaded as:
from datasets import load_dataset
ds = load_dataset("navinavi029/my-distiset-1e19c746", "default")
Or simply as it follows, since there's only one configuration and is named default:
from datasets import load_dataset
ds = load_dataset("navinavi029/my-distiset-1e19c746")
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