| --- |
| library_name: peft |
| base_model: Lemoooon/LexMatcher_8B |
| language: |
| - de |
| - en |
| tags: |
| - machine-translation |
| - lora |
| - terminology |
| - glossary |
| - lexmatcher |
| - vllm |
| license: apache-2.0 |
| --- |
| |
| # MT-explain: LoRA Adapter for Terminology-Aware Machine Translation |
| A specialized LoRA adapter that **generates a terminology list (术语表) before producing the final translation** for high-accuracy, consistent machine translation. |
|
|
| ## Model Details |
| - **Model Type**: LoRA Adapter for LLMs |
| - **Base Model**: [LexMatcher_8B](https://huggingface.co/Lemoooon/LexMatcher_8B) |
| - **Current Language Support**: German → English (De-En), Chinese → English (Zh-En) |
| - **Core Function**: Terminology glossary generation + final translation |
| - **Inference Engine**: Optimized for vLLM with LoRA enabled |
|
|
| ## Model Description |
| MT-explain is a fine-tuned LoRA adapter built on top of LexMatcher_8B. It follows a unique two-step generation process: |
| 1. First, generate a terminology list for the input source text |
| 2. Then, generate the final translation using the terminology for consistency |
| |
| This ensures domain-specific terms, proper nouns, and technical vocabulary are translated accurately and consistently. |
| |
| ## Deployment & Inference Guide |
| |
| ### 1. Prepare Local Files |
| Download both the base model and adapter to your local machine: |
| - Base model path: `./LexMatcher_8B` |
| - LoRA adapter path: `./MT-explain` |
|
|
| ### 2. Install Dependencies |
| ```bash |
| pip install vllm>=0.4.0 transformers peft torch |
| ``` |
|
|
| ### 3. Start vLLM Server (with LoRA) |
| Run this exact command: |
| ``` |
| vllm serve ./LexMatcher_8B \ |
| --host 0.0.0.0 \ |
| --port 8000 \ |
| --dtype auto \ |
| --enable-lora \ |
| --lora-modules my-lora=./MT-explain \ |
| --gpu-memory-utilization 0.90 \ |
| --max-model-len 1024 |
| ``` |
|
|
| ### 4. Test Inference |
| The model will automatically output:Terminology List → Final Translation |
|
|
