---

pipeline_tag: text-classification

library_name: transformers

tags:

- sentiment-analysis

- text-classification

- nlp

- transformers

---

 

# 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

 

```python

from transformers import pipeline

 

classifier = pipeline(

    "sentiment-analysis",

    model="srivarthini/sentiment-analyzer"

)

 

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