
## Overview

This model was trained with data from https://registry.opendata.aws/helpful-sentences-from-reviews/ to predict how "helpful" a review is.

The model was fine-tuned from the `distilbert-base-uncased` model

### Labels
LABEL_0 - Not helpful  
LABEL_1 - Helpful  

### How to use

The following code shows how to make a prediction with this model

```python
from transformers import (
    AutoTokenizer,
    AutoModelForSequenceClassification,
    TextClassificationPipeline,
)

tokenizer = AutoTokenizer.from_pretrained("banjtheman/distilbert-base-uncased-helpful-amazon")

model = AutoModelForSequenceClassification.from_pretrained(
    "banjtheman/distilbert-base-uncased-helpful-amazon"
)

pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer)

result = pipe("This was a Christmas gift for my grandson.")

print(result)

#[{'label': 'LABEL_0', 'score': 0.998775064945221}]
# This is NOT A HELPFUL comment

```
{"license": "apache-2.0"}
transformers pytorch distilbert text-classification license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #text-classification #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 


## Overview

This model was trained with data from URL to predict how "helpful" a review is.

The model was fine-tuned from the 'distilbert-base-uncased' model

### Labels
LABEL_0 - Not helpful  
LABEL_1 - Helpful  

### How to use

The following code shows how to make a prediction with this model


## Overview

This model was trained with data from URL to predict how "helpful" a review is.

The model was fine-tuned from the 'distilbert-base-uncased' model ### Labels
LABEL_0 - Not helpful  
LABEL_1 - Helpful ### How to use

The following code shows how to make a prediction with this model
TAGS
#transformers #pytorch #distilbert #text-classification #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ## Overview

This model was trained with data from URL to predict how "helpful" a review is.

The model was fine-tuned from the 'distilbert-base-uncased' model ### Labels
LABEL_0 - Not helpful  
LABEL_1 - Helpful ### How to use

The following code shows how to make a prediction with this model
passage: TAGS
#transformers #pytorch #distilbert #text-classification #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
## Overview

This model was trained with data from URL to predict how "helpful" a review is.

The model was fine-tuned from the 'distilbert-base-uncased' model### Labels
LABEL_0 - Not helpful  
LABEL_1 - Helpful### How to use

The following code shows how to make a prediction with this model