--- license: mit language: - en metrics: - accuracy 97.9% base_model: - distilbert/distilbert-base-uncased pipeline_tag: text-classification --- # Last Name Classification Model [![Support](https://img.shields.io/badge/Support-Us-brightgreen)](https://nowpayments.io/donation/Vishodi) A Transformer-based classifier that checks if a provided last name is likely to be **real** (LABEL_1) or **fake** (LABEL_0). This can be helpful in validating contact form submissions, preventing bot entries, or for general name classification tasks. ## Table of Contents - [Project Structure](#project-structure) - [Installation](#installation) - [Usage](#usage) - [Support Me](#support-me) - [License](#license) ## Project Structure ```plaintext Last_Name_Prediction/ ├── .gitattributes ├── README.md ├── config.json ├── model.safetensors ├── requirements.txt ├── special_tokens_map.json ├── tokenizer.json ├── tokenizer_config.json └── vocab.txt ``` ## Installation 1. **Clone the Repository:** ```bash git clone https://github.com/Vishodi/Last-Name-Classification.git ``` 2. **Set Up the Environment:** Install the required packages using pip: ```bash pip install -r requirements.txt ``` ## Usage ```python from transformers import pipeline # Replace with your model repository model_dir = "vishodi/Last-Name-Classification" # Load the model pipeline with authentication classifier = pipeline( "text-classification", model=model_dir, tokenizer=model_dir, ) # Test the model test_names = ["musk", "zzzzzz", "uhyhu", "trump"] for name in test_names: result = classifier(name) label = result[0]['label'] score = result[0]['score'] print(f"Name: {name} => Prediction: {label}, Score: {score:.4f}") ``` **Output:** ``` Name: musk => Prediction: LABEL_1, Score: 0.9167 Name: zzzzzz => Prediction: LABEL_0, Score: 0.9991 Name: uhyhu => Prediction: LABEL_0, Score: 0.9944 Name: trump => Prediction: LABEL_1, Score: 0.9998 ``` ## Support Us [![Support Us](https://img.shields.io/badge/Support-Us-brightgreen)](https://nowpayments.io/donation/Vishodi) ## License This project is licensed under the MIT License.