GlinerRust [WIP]

GlinerRust is a Rust library for Named Entity Recognition (NER) using ONNX models. It provides a simple and efficient way to perform NER tasks on text data using pre-trained models.

Features

• Easy-to-use API for Named Entity Recognition
• Support for custom ONNX models
• Asynchronous processing for improved performance
• Configurable parameters for fine-tuning

Installation

Add this to your Cargo.toml:

[dependencies]
glinerrust = { git = "https://github.com/srv1n/Gliner-rs.git" }

Alternatively, you can clone the repository and use it locally:

git clone https://github.com/srv1n/Gliner-rs.git
cd Gliner-rs

Then, in your Cargo.toml, add:

[dependencies]
glinerrust = { path = "path/to/Gliner-rs" }

Running the Example

To run the provided example:

1. Ensure you have Rust and Cargo installed on your system.
2. Clone this repository:

   git clone https://github.com/yourusername/glinerrust.git
   cd glinerrust
   

3. Download the required model and tokenizer files:
   • Place tokenizer.json in the project root
   • Place model_quantized.onnx in the project root
4. Run the example using Cargo:

   cargo run --example basic_usage
   

Note: Make sure you have the necessary ONNX model and tokenizer files before running the example. The specific model and tokenizer files required depend on your use case and the pre-trained model you're using.

Configuration

The InitConfig struct allows you to customize the behavior of GlinerRust:

• tokenizer_path: Path to the tokenizer JSON file
• model_path: Path to the ONNX model file
• max_width: Maximum width for processing (optional)
• num_threads: Number of threads to use for inference (optional)

API Reference

Gliner

The main struct for interacting with the GlinerRust library.

Methods

• new(config: InitConfig) -> Self: Create a new Gliner instance
• initialize(&mut self) -> Result<(), GlinerError>: Initialize the Gliner instance
• inference(&self, input_texts: &[String], entities: &[String], ignore_subwords: bool, threshold: f32) -> Result<Vec<InferenceResultSingle>, GlinerError>: Perform inference on the given input texts

InitConfig

Configuration struct for initializing a Gliner instance.

EntityResult

Represents a single entity detected in the text.

InferenceResultSingle

Represents the inference result for a single input text.

InferenceResultMultiple

Represents the inference results for multiple input texts.

Error Handling

The library uses a custom GlinerError enum for error handling, which includes:

• InitializationError: Errors that occur during initialization
• InferenceError: Errors that occur during the inference process

Performance Considerations

• The num_threads option in InitConfig allows you to control the number of threads used for inference. Adjust this based on your system's capabilities.
• The max_width option can be used to limit the maximum input size. This can help manage memory usage for large inputs.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the project
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Support

If you encounter any issues or have questions, please file an issue on the GitHub repository.