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---
base_model: google/gemma-2b
library_name: peft
pipeline_tag: text-generation
tags:
- sentiment-analysis
- lora
- transformers
- peft
---
# Sentiment Analyzer
A fine-tuned sentiment analysis model developed and shared by **Pavithrapn-01**.
This model is designed to analyze text and classify sentiment efficiently using a lightweight fine-tuning approach.
---
## Model Details
### Model Description
This model is a **sentiment analysis system** built by fine-tuning the **google/gemma-2b** base model using **LoRA (Low-Rank Adaptation)**.
It is optimized for understanding emotional polarity in text such as **positive, negative, or neutral sentiment**.
- **Developed by:** Pavithra PN
- **Shared by:** Pavithrapn-01
- **Model type:** Text Generation / Sentiment Analysis
- **Language(s):** English
- **License:** Open-source (same as base model)
- **Finetuned from model:** google/gemma-2b
---
## Model Sources
- **Repository:** Pavithrapn-01/sentiment-analyzer
- **Base Model:** google/gemma-2b
---
## Uses
### Direct Use
- Sentiment analysis of user reviews
- Opinion mining from social media text
- Feedback and survey analysis
- Educational and academic projects
### Downstream Use
- Can be integrated into chatbots
- Can be used in recommendation systems
- Can be further fine-tuned for domain-specific sentiment tasks
### Out-of-Scope Use
- Medical or legal decision-making
- High-risk or safety-critical applications
- Multilingual sentiment analysis (English only)
---
## Bias, Risks, and Limitations
- The model may reflect biases present in the training data
- Performance may vary on slang, sarcasm, or ambiguous text
- Best suited for short to medium-length text inputs
### Recommendations
Users should validate outputs before deploying the model in real-world applications and avoid using it for sensitive decision-making.
---
## How to Get Started with the Model
```python
from transformers import pipeline
classifier = pipeline("sentiment-analysis", model="Pavithrapn-01/sentiment-analyzer")
result = classifier("I really enjoyed using this application!")
print(result)
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