README.md

metadata

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

pip install -r requirements.txt

Usage

1. Run the application:

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

   • Based on BERT multilingual model
   • Fine-tuned on OpenAlex data
   • Supports multiple languages

2. 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
• Hugging Face Spaces