The following steps need to be followed to deploy Seed-X-7B:
- environmental preparation: Clone the project repository via Git and create a conda virtual environment for Python 3.10
- Dependent Installation: Install all Python libraries listed in requirements.txt, and recommend installing Flash Attention additionally to accelerate inference.
- Model Download: Download model weights from Hugging Face (recommended version Seed-X-PPO-7B)
Use the process:
- single-sentence translation: Load the model through the vLLM library and enter the text to be translated (the target language needs to be specified with tags such as )
- batch translation: Utilizes vLLM's batch processing capabilities to process multiple translation requests in parallel
- complex translation: Enable Chained Reasoning (CoT) mode, where the model analyzes the sentence structure before generating the translation
Hardware Recommendations:
- Single GPU reasoning requires at least H100-80G video memory
- Processing high-resolution content suggests using 4 H100-80G parallel computing
This answer comes from the articleSeed-X-7B: Efficient Multilingual Translation of Large ModelsThe
May not be reproduced without permission:AI productivity tools " How to deploy and use Seed-X-7B for translation tasks?
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