sentiment-analyzer

Sentiment Analyzer

This repository contains a sentiment analysis model for classifying text based on sentiment polarity (e.g., positive, negative, neutral).

The model is intended for experimentation, learning, and basic NLP sentiment classification tasks.

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Model Details

Model Description

• Task: Sentiment Analysis / Text Classification

• Model type: Transformer-based text classification model

• Pipeline type: Text Classification

• Language: English

• Framework: Hugging Face Transformers

Note: Detailed architecture and training configuration were not explicitly documented at the time of upload.

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Developed By

• Author: Srivarthini

License

• License information has not been specified.

  Users should verify licensing before using this model in production.

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Intended Uses

Direct Use

This model can be used for:

• Sentiment classification of short text

• Customer review analysis

• Feedback or survey sentiment analysis

• Educational and demonstration purposes

Downstream Use

• Can be integrated into NLP pipelines

• Can be further fine-tuned on domain-specific datasets

Out-of-Scope Use

• Medical, legal, or financial decision-making

• Safety-critical or high-risk automated systems

• Content moderation without human oversight

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How to Get Started

Example Usage

from transformers import pipeline

 

classifier = pipeline(

    "sentiment-analysis",

    model="srivarthini/sentiment-analyzer"

)

 

classifier("The service was excellent and very fast.")