EuroBERT-210m
| Property | Value |
|---|---|
| Parameter Count | 210 Million |
| Model Type | Multilingual Encoder |
| License | Apache 2.0 |
| Maximum Sequence Length | 8,192 tokens |
| Supported Languages | 15 languages |
| Model Hub | HuggingFace |
What is EuroBERT-210m?
EuroBERT-210m is part of the EuroBERT family of multilingual encoder models, specifically designed to handle multiple languages, mathematics, and code. As the compact version in the series, it offers an efficient balance between performance and resource requirements, supporting sequences of up to 8,192 tokens.
Implementation Details
The model can be easily implemented using the Transformers library (v4.48.0+). It supports Flash Attention 2 for enhanced efficiency on compatible GPUs. The model uses a masked language modeling approach and can be fine-tuned with specific learning rates optimized for different tasks.
- Supports masked language modeling with efficient prediction capabilities
- Compatible with Flash Attention 2 for improved performance
- Implements standard transformer architecture with optimized parameters
- Fine-tuning hyperparameters include 0.1 warmup ratio and linear learning rate scheduling
Core Capabilities
- Multilingual text processing across 15 languages
- Strong performance in retrieval tasks
- Classification and regression capabilities
- Code and mathematics task handling
- Competitive performance against larger models
Frequently Asked Questions
Q: What makes this model unique?
EuroBERT-210m stands out for its ability to handle multiple languages, mathematics, and code while maintaining strong performance despite its relatively compact size. It shows competitive results against larger models, especially in specialized tasks.
Q: What are the recommended use cases?
The model is well-suited for multilingual applications including text classification, retrieval tasks, quality estimation, and summary evaluation. It's particularly effective for code-related tasks and mathematical applications, with specific fine-tuning parameters available for each use case.
