Update README.md

README.md

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----
-license: apache-2.0
----
+---
+tags:
+- text-classification
+- distilbert
+- political-bias
+- safetensors
+license: apache-2.0
+---
+
+# political-bias-classifier
+[![Hugging Face Model](https://img.shields.io/badge/Model%20Type-DistilBERT-blue.svg)](https://huggingface.co/models?search=distilbert) 
+[![License](https://img.shields.io/badge/License-Apache%202.0-green.svg)](https://www.apache.org/licenses/LICENSE-2.0)
+
+***
+
+## 📖 Model Description
+
+The **political-bias-classifier** is a fine-tuned **DistilBERT** model designed for **text classification** to identify and categorize political bias within a given text.
+
+This model is intended to analyze the political leaning expressed in textual content, such as news headlines, articles, or social media commentary.
+
+| Detail | Value |
+| :--- | :--- |
+| **Base Model** | DistilBERT |
+| **Model Type** | Text Classification (Sequence Classification) |
+| **Weights Format**| Safetensors (`model.safetensors`) |
+| **License** | Apache-2.0 |
+| **File Size** | ~268 MB |
+
+***
+
+## 🚀 Usage
+
+You can easily use this model for inference with the Hugging Face `transformers` library.
+
+### Using the Pipeline
+
+The simplest way to get a prediction is by using the `pipeline` abstraction:
+
+```python
+from transformers import pipeline
+
+# Initialize the classifier pipeline
+classifier = pipeline(
+    "text-classification", 
+    model="Arstacity/political-bias-classifier"
+)
+
+# Example text for analysis
+text_to_analyze = "The new trade bill is a crucial step towards economic growth, despite the opposition's claims of cronyism."
+
+# Get the prediction
+result = classifier(text_to_analyze)
+
+print(result)
+# Example Output Format (Actual labels and scores will vary): 
+# [{'label': 'RIGHT_LEANING', 'score': 0.9542}]
+```
+
+### Direct Model Loading
+
+For more control, you can load the tokenizer and model directly:
+
+```python
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+model_name = "Arstacity/political-bias-classifier"
+
+# Load the tokenizer
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+# Load the model
+model = AutoModelForSequenceClassification.from_pretrained(model_name)
+
+# You are now ready to perform tokenization and inference.
+```
+***
+## Files in Repository
+
+This repository contains all the necessary files for the DistilBERT model and tokenizer:
+
+| File Name | Description |
+| :--- | :--- |
+| **model.safetensors** | The main model weights file (268 MB). |
+| **config.json** | Configuration file for the model architecture |
+| **vocab.txt**| Vocabulary file for the tokenizer |
+| **tokenizer.json** | The tokenizer configuration file |
+| **tokenizer_config.json** | Tokenizer metadata |
+| **special_tokens_map.json** | Mapping for special tokens. |
+***
+
+License: Apache 2.0
+---