COMET-partial
| Property | Value |
|---|---|
| Author | zouharvi |
| Paper | Early-Exit and Instant Confidence Translation Quality Estimation (2025) |
| Repository | https://github.com/zouharvi/COMET-early-exit |
| Model Page | https://huggingface.co/zouharvi/COMET-partial |
What is COMET-partial?
COMET-partial is an innovative machine translation evaluation model that extends the capabilities of traditional translation quality estimation by enabling the assessment of incomplete translations. Based on the COMET-early-exit framework, it represents a significant advancement in translation quality assessment by allowing real-time evaluation of translation prefixes.
Implementation Details
The model is implemented as a fork of the original Unbabel's COMET, though it maintains its own unique compatibility requirements. It requires specific installation through pip using the COMET-early-exit repository or through an editable installation mode. The implementation supports batch processing and GPU acceleration for efficient scoring of translation segments.
- Custom installation requirements through specific repository
- Support for batch processing with configurable batch sizes
- GPU acceleration capabilities
- Scoring capability for partial translations
Core Capabilities
- Evaluation of incomplete translation segments
- Consistent scoring across translation prefixes
- High-precision scoring system (outputs in 89-90 range for quality translations)
- Batch processing support for efficient evaluation
- Compatible with both complete and partial translation assessment
Frequently Asked Questions
Q: What makes this model unique?
COMET-partial's unique feature is its ability to evaluate incomplete translations or translation prefixes, which is not possible with traditional translation quality estimation models. This makes it particularly valuable for real-time translation assessment and incremental translation scenarios.
Q: What are the recommended use cases?
The model is ideal for scenarios requiring real-time translation quality assessment, development of interactive translation systems, and evaluation of partial translations during the translation process. It's particularly useful for translation quality monitoring in streaming or incremental translation settings.
