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.
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.
Developed By
- Author: Srivarthini
License
License information has not been specified.
Users should verify licensing before using this model in production.
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
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.")