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---
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") |