AmbatronBERTa
| Property | Value |
|---|---|
| Parameter Count | 105M parameters |
| Model Type | Thai Language Model |
| Base Architecture | WangchanBERTa |
| License | Unknown |
| Tensor Type | F32 |
What is AmbatronBERTa?
AmbatronBERTa is a specialized Thai language model developed by researchers at King Mongkut's University of Technology North Bangkok. Built upon the WangchanBERTa architecture, it has been specifically fine-tuned for text classification tasks using a dataset of over 3,000 research papers. The model represents a significant advancement in Thai language processing capabilities.
Implementation Details
The model implements a transformer-based architecture with 105M parameters, utilizing F32 tensor types for computation. It's provided in Safetensors format and builds upon the airesearch/wangchanberta-base-att-spm-uncased foundation.
- Transformer-based architecture optimized for Thai language
- Fine-tuned on 3,000+ research papers
- Implements specialized tokenization for Thai text
- Supports multiple classification tasks
Core Capabilities
- Research Paper Classification
- Document Organization
- Sentiment Analysis in Thai
- Theme-based Content Categorization
Frequently Asked Questions
Q: What makes this model unique?
AmbatronBERTa's uniqueness lies in its specialized fine-tuning for Thai language text classification, particularly in academic and research contexts. The model's training on a substantial corpus of research papers makes it particularly effective for scholarly content classification.
Q: What are the recommended use cases?
The model excels in categorizing Thai language academic papers, performing sentiment analysis on Thai text, and organizing documents by themes. It's particularly well-suited for academic institutions and research organizations working with Thai language content.
