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---
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license: apache-2.0
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---
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## Overview
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This model was trained with data from https://registry.opendata.aws/helpful-sentences-from-reviews/ to predict how "helpful" a review is.
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The model was fine-tuned from the `distilbert-base-uncased` model
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### Labels
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LABEL_0 - Not helpful
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LABEL_1 - Helpful
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### How to use
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The following code shows how to make a prediction with this model
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```python
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from transformers import (
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AutoTokenizer,
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AutoModelForSequenceClassification,
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TextClassificationPipeline,
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)
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tokenizer = AutoTokenizer.from_pretrained("banjtheman/distilbert-base-uncased-helpful-amazon")
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model = AutoModelForSequenceClassification.from_pretrained(
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"banjtheman/distilbert-base-uncased-helpful-amazon"
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)
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pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer)
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result = pipe("This was a Christmas gift for my grandson.")
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print(result)
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#[{'label': 'LABEL_0', 'score': 0.998775064945221}]
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# This is NOT A HELPFUL comment
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``` |
