DanbotNL-2408-260M
| Property | Value |
|---|---|
| Parameter Count | 260M |
| Base Model | modernbert-ja-130m |
| License | Apache-2.0 |
| Developer | Plat |
| Languages | Japanese, English |
| Knowledge Cutoff | 2024/08/31 |
What is DanbotNL-2408-260M?
DanbotNL-2408-260M is a specialized translation model designed to convert natural language descriptions into Danbooru tags. It serves as a bridge between human-readable descriptions and the structured tagging system used in the Danbooru image database. The model supports both Japanese and English inputs and can generate precise tag translations with various levels of detail.
Implementation Details
Built on the modernbert-ja-130m architecture and fine-tuned with Dart v3 SFT, this model implements a sophisticated translation system with multiple operating modes. It utilizes a template-based approach for controlling output characteristics and supports both exact and approximate translation modes.
- Leverages transformer architecture with 260M parameters
- Implements customizable aspect ratio controls
- Supports multiple content rating levels
- Features adjustable output length settings
- Uses synthetic training data from danbooru-2408-blind-captions
Core Capabilities
- Precise translation of natural language to Danbooru tags
- Support for both exact and approximate translation modes
- Customizable output length from very_short to very_long
- Handling of different aspect ratios and content ratings
- Extensive tag categorization (copyright, character, general)
Frequently Asked Questions
Q: What makes this model unique?
DanbotNL-2408-260M stands out for its specialized ability to translate natural language descriptions into structured Danbooru tags, supporting both Japanese and English inputs. Its template-based system allows for precise control over output characteristics, making it particularly valuable for image tagging and classification tasks.
Q: What are the recommended use cases?
The model is ideal for automated image tagging systems, content organization platforms, and applications requiring precise translation of natural language descriptions into standardized Danbooru tags. It's particularly useful in scenarios requiring both Japanese and English language support with controlled output formatting.
