This repository provides a Japanese GPT-2 language model, trained on a diverse Japanese corpus. It's designed for researchers and developers interested in Japanese text generation, offering capabilities for generating natural-sounding text, continuing prompts, and transforming text into vector representations.

How It Works

The project leverages the GPT-2 architecture, fine-tuned with a substantial Japanese corpus. This approach allows for the generation of contextually relevant and coherent Japanese text, outperforming models trained solely on Wikipedia. The model can produce text with elements from blog posts, news releases, and encyclopedic entries.

Quick Start & Requirements

• Install: git clone https://github.com/tanreinama/gpt2-japanese
• Download models: wget https://www.nama.ne.jp/models/gpt2ja-medium.tar.bz2
• Run generation: python3 gpt2-generate.py --model gpt2ja-medium --num_generate 1
• Dependencies: Python 3, TensorFlow 1.x/2.x.
• Demo: Sakamoto's AI lab

Highlighted Details

• Generates natural Japanese text, superior to Wikipedia-only trained models.
• Supports context-based generation for more coherent outputs.
• Includes utilities for text vectorization (gpt2-transform.py) and text scoring (gpt2-score.py).
• Provides a fine-tuning script (run_finetune.py) for custom datasets.

Maintenance & Community

The project has a GitHub sponsor program and a successor project, GPTSAN, is recommended for new development.

Licensing & Compatibility

The repository does not explicitly state a license. Users should verify compatibility for commercial or closed-source use.

Limitations & Caveats

The README mentions a successor project, GPTSAN, suggesting this repository may be in maintenance mode or superseded. No specific license is listed, which could be a concern for commercial adoption.