💻 programming

DRT-o1

Deep reasoning translation model, optimizing neural machine translation through long thinking chain.

#natural language processing
#deep learning
#neural machine translation
#multi-agent framework
#long chain of thinking
DRT-o1

Product Details

DRT-o1 is a neural machine translation model that optimizes the translation process through long thinking chains. The model mines English sentences containing metaphors or metaphors and adopts a multi-agent framework (including translators, consultants, and evaluators) to synthesize long-thinking machine translation samples. DRT-o1-7B and DRT-o1-14B are large language models trained based on Qwen2.5-7B-Instruct and Qwen2.5-14B-Instruct. The main advantage of DRT-o1 is its ability to handle complex language structures and deep semantic understanding, which are crucial to improving the accuracy and naturalness of machine translation.

Main Features

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• Long-thinking chain translation: Optimize neural machine translation through long-thinking chain reasoning.
2
• Multi-agent framework: It includes three agents: translator, consultant and evaluator, working together to complete the translation task.
3
• Complex language structure processing: Ability to process complex English sentences containing metaphors or metaphors.
4
• Large language model: trained based on Qwen2.5-7B-Instruct and Qwen2.5-14B-Instruct.
5
• High accuracy and naturalness: Improve translation quality through deep semantic understanding.
6
• Open source model checkpoints: Provides model checkpoints for the convenience of researchers and developers.
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• Huggingface Transformers support: Models can be easily deployed and called on the Huggingface platform.

How to Use

1
1. Visit the Huggingface official website and search for the DRT-o1 model.
2
2. Download and install the Huggingface Transformers library.
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3. Use Python code to load the DRT-o1 model and tokenizer.
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4. The text to be input can be an English sentence with a complex structure.
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5. Enter the text into the model and obtain the translation results generated by the model.
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6. Analyze the translation results and perform post-processing or adjust model parameters as needed to optimize translation quality.
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7. Apply the optimized translation results to actual translation tasks.

Target Users

The target audience of DRT-o1 is researchers and developers in the field of natural language processing, as well as enterprises that require high-quality machine translation. Because it can handle complex language structures and deep semantic understanding, it is particularly suitable for users who need to accurately translate documents in professional fields such as literary works and legal documents.

Examples

Case 1: Use DRT-o1 to translate English literary works containing metaphors into Chinese to maintain the literary charm and deep meaning of the original text.

Case 2: The legal industry uses DRT-o1 to translate legal documents to ensure the accuracy and professionalism of the translation.

Case 3: DRT-o1 is used in the education field to translate academic materials to help researchers obtain the latest international research results.

Quick Access

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Categories

💻 programming
› translate
› Model training and deployment

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