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---
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.
---
## 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
```python
from transformers import pipeline
classifier = pipeline(
"sentiment-analysis",
model="srivarthini/sentiment-analyzer"
)
classifier("The service was excellent and very fast.") |