DilipKY/espa-ai1

Model Card for ESPA AI

ESPA AI is a text classification model fine-tuned on the IMDb dataset using DistilBERT. It is designed to classify movie reviews as either positive or negative.

Model Details

Model Description

This model uses the DistilBERT architecture, a smaller, faster version of BERT, to perform sentiment analysis on text data. It has been fine-tuned on the IMDb dataset for binary classification (positive or negative reviews).

• Developed by: DilipKY
• Funded by: [Optional Information]
• Model type: Transformer-based model (DistilBERT)
• Language(s): English
• License: MIT License
• Finetuned from model: distilbert-base-uncased

Model Sources

• Repository: DilipKY/espa-ai
• Paper: DistilBERT: A smaller, faster, cheaper version of BERT

Uses

Direct Use

This model can be used to classify text data into positive or negative categories. It is useful for sentiment analysis in applications like customer feedback analysis, review classification, etc.

from transformers import pipeline

# Load pre-trained model from Hugging Face
classifier = pipeline("text-classification", model="DilipKY/espa-ai")

# Test on a sample review
sample_text = "This movie was amazing! The plot was so engaging and the acting was superb."
result = classifier(sample_text)
print(result)