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README.md
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- distilbert/distilbert-base-uncased
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pipeline_tag: text-classification
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---
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[](https://www.example.com/donate?crypto=YOUR_CRYPTO_ID)
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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.
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---
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## Table of Contents
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- [Project Structure](#project_structure)
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- [Installation](#installation)
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- [Usage](#usage)
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- [Support Me](#support-me)
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- [License](#license)
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## Project Structure
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```
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Last_Name_Prediction/
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βββ .gitattributes
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βββ README.md
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βββ tokenizer.json
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βββ tokenizer_config.json
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βββ vocab.txt
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```
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---
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## Installation
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1. **Clone the Repository:**
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cd name-validation-ai
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```
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2. **Set Up the Environment:**
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Install the required packages using pip:
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```
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---
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## Usage
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Python
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```python
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from transformers import pipeline
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# Replace with your model
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model_dir = "/
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# Load the model pipeline
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classifier = pipeline(
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"text-classification",
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model=model_dir,
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tokenizer=model_dir,
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framework="pt"
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)
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# Test the model
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test_names = ["
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for name in test_names:
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result = classifier(name)
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label = result[0]['label']
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score = result[0]['score']
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print(f"Name: {name} => Prediction: {label}, Score: {score:.4f}")
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```
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Name: musk => Prediction: LABEL_1, Score: 0.9167
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Name: zzzzzz => Prediction: LABEL_0, Score: 0.9991
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Name: uhyhu => Prediction: LABEL_0, Score: 0.9944
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Name: trump => Prediction: LABEL_1, Score: 0.9998
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```
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## Support Me
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If you find this project helpful and would like to support my work, please consider donating using crypto.
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<img src="https://img.shields.io/badge/Support-Me-brightgreen" alt="Support Me">
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</a>
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---
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## License
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This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
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---
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*Contributions, issues, and feature requests are welcome! Feel free to fork the repository and open a pull request.*
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```
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- distilbert/distilbert-base-uncased
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pipeline_tag: text-classification
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---
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# Last Name Classification Model
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[](https://nowpayments.io/donation/Vishodi)
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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.
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## Table of Contents
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- [Project Structure](#project-structure)
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- [Installation](#installation)
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- [Usage](#usage)
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- [Support Me](#support-me)
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- [License](#license)
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## Project Structure
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```plaintext
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Last_Name_Prediction/
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βββ .gitattributes
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βββ README.md
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βββ tokenizer.json
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βββ tokenizer_config.json
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βββ vocab.txt
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```
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## Installation
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1. **Clone the Repository:**
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```bash
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git clone https://github.com/Vishodi/Last-Name-Classification.git
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```
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2. **Set Up the Environment:**
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Install the required packages using pip:
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```bash
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pip install -r requirements.txt
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```
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## Usage
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```python
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from transformers import pipeline
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# Replace with your model repository
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model_dir = "vishodi/Last-Name-Classification"
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# Load the model pipeline with authentication
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classifier = pipeline(
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"text-classification",
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model=model_dir,
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tokenizer=model_dir,
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)
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# Test the model
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test_names = ["kiara", "zzzzzz", "uhyhu", "trump"]
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for name in test_names:
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result = classifier(name)
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label = result[0]['label']
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score = result[0]['score']
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print(f"Name: {name} => Prediction: {label}, Score: {score:.4f}")
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```
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**Output:**
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```
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Name: musk => Prediction: LABEL_1, Score: 0.9167
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Name: zzzzzz => Prediction: LABEL_0, Score: 0.9991
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Name: uhyhu => Prediction: LABEL_0, Score: 0.9944
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Name: trump => Prediction: LABEL_1, Score: 0.9998
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```
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## Support Me
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If you find this project helpful and would like to support my work, please consider donating using crypto.
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[](https://nowpayments.io/donation/Vishodi)
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## License
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This project is licensed under the MIT License. See the LICENSE file for details.
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