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
from transformers import pipeline
classifier = pipeline(
"sentiment-analysis",
model="New12fef/np-ai-model"
)
classifier("I enjoy learning artificial intelligence")
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