---
library_name: transformers
tags:
- sentiment-analysis
- text-classification
- nlp
- beginner
---

# Model Card for New12fef/np-ai-model

This model is a **sentiment analysis model** that classifies English text as **Positive** or **Negative**.  
It is designed mainly for **learning, experimentation, and academic projects**.

---

## Model Details

### Model Description

This is a Transformer-based sentiment analysis model fine-tuned using the 🤗 Transformers library.  
The model predicts whether a given English sentence expresses a positive or negative sentiment.

- **Developed by:** New12fef  
- **Funded by:** Not applicable  
- **Shared by:** New12fef  
- **Model type:** Transformer-based text classification model  
- **Language(s) (NLP):** English  
- **License:** Apache 2.0  
- **Finetuned from model:** distilbert-base-uncased  

### Model Sources

- **Repository:** https://huggingface.co/New12fef/np-ai-model  
- **Paper:** Not applicable  
- **Demo:** Not available  

---

## Uses

### Direct Use

This model can be used directly for:
- Sentiment analysis of short English sentences
- Learning Natural Language Processing (NLP)
- College mini-projects and demonstrations
- Beginner experimentation with Transformers

### Downstream Use

The model can be further fine-tuned or integrated into:
- Chatbots
- Feedback or review analysis systems
- Educational AI applications

### Out-of-Scope Use

This model is **not suitable** for:
- Medical, legal, or financial decision-making
- High-risk or real-world production systems
- Multilingual sentiment analysis
- Understanding sarcasm or complex emotional context

---

## Bias, Risks, and Limitations

- Trained on a **small custom dataset**
- Performance may degrade on:
  - Long paragraphs
  - Slang or informal language
  - Sarcasm
- Predictions may reflect biases present in the training data

### Recommendations

Users should:
- Use this model for **educational purposes only**
- Fine-tune with a larger and more diverse dataset for better accuracy
- Avoid using it in critical applications

---

## How to Get Started with the Model

```python
from transformers import pipeline

classifier = pipeline(
    "sentiment-analysis",
    model="New12fef/np-ai-model"
)

classifier("I enjoy learning artificial intelligence")