New12fef
/

np-ai-model

@@ -1,199 +1,95 @@
 ---
 library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
 ## Model Details
 ### Model Description
-<!-- Provide a longer summary of what this model is. -->
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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 ## How to Get Started with the Model
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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")