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---
title: Openalex Topic Classification
emoji: 🏢
colorFrom: pink
colorTo: red
sdk: gradio
sdk_version: 5.23.1
app_file: app.py
pinned: false
license: mit
short_description: OpenAlex/bert-base-multilingual-cased-finetuned-openalex-top
---
# OpenAlex Topic Classification
This application allows you to classify academic texts into different topics using machine learning models trained with OpenAlex data.
## Features
- Classification of academic texts into multiple topics
- Uses two different models for more robust classification
- Easy-to-use web interface
- Support for structured title and abstract format
## Requirements
- Python 3.7+
- Gradio 5.23.1
- Transformers (Hugging Face)
## Installation
```bash
pip install -r requirements.txt
```
## Usage
1. Run the application:
```bash
python app.py
```
2. Open your browser at the address shown in the console (usually http://localhost:7860)
3. Enter your text in the format:
```
<TITLE> Your title here
<ABSTRACT> Your abstract here
```
4. Select the number of classifications you want to see (top_k)
5. Click "Submit" to get the results
## Models
The application uses two different models:
1. [OpenAlex/bert-base-multilingual-cased-finetuned-openalex-topic-classification-title-abstract](https://huggingface.co/OpenAlex/bert-base-multilingual-cased-finetuned-openalex-topic-classification-title-abstract)
- Based on BERT multilingual model
- Fine-tuned on OpenAlex data
- Supports multiple languages
2. [albertmartinez/openalex-topic-classification-title-abstract](https://huggingface.co/albertmartinez/openalex-topic-classification-title-abstract)
- Based on BERT multilingual model
- Fine-tuned on OpenAlex data (https://huggingface.co/datasets/albertmartinez/openalex-topic-title-abstract)
- Supports multiple languages
## License
MIT
## References
- [OpenAlex](https://openalex.org/)
- [Hugging Face Spaces](https://huggingface.co/docs/hub/spaces-config-reference) |