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---
license_name: openmdw
license_link: LICENSE
datasets:
- fka/awesome
metrics:
- accuracy
- character
pipeline_tag: text-classification
## Introduction
We are excited to introduce **Seed-X**, a powerful series of open-source multilingual translation language models, including an instruction model, a reinforcement learning model, and a reward model. It pushes the boundaries of translation capabilities within 7 billion parameters.
We develop Seed-X as an accessible, off-the-shelf tool to support the community in advancing translation research and applications:
* **Exceptional translation capabilities**: Seed-X exhibits state-of-the-art translation capabilities, on par with or outperforming ultra-large models like Gemini-2.5, Claude-3.5, and GPT-4, as validated by human evaluations and automatic metrics.
* **Deployment and inference-friendly**: With a compact 7B parameter count and mistral architecture, Seed-X offers outstanding translation performance in a lightweight and efficient package, ideal for deployment and inference.
* **Broad domain coverage**: Seed-X excels on a highly challenging translation test set spanning diverse domains, including the internet, science and technology, office dialogues, e-commerce, biomedicine, finance, law, literature, and entertainment.
This repo contains the **Seed-X-Instruct** model, with the following features:
* Type: Causal language models
* Training Stage: Pretraining & Post-training
* Support: Multilingual translation among 28 languages
| Languages | Abbr. | Languages | Abbr. | Languages | Abbr. | Languages | Abbr. |
| ----------- | ----------- |-----------|-----------|-----------|-----------| -----------|-----------|
|Arabic | ar |French | fr | Malay | ms | Russian | ru |
|Czech | cs |Croatian | hr | Norwegian Bokmal | nb | Swedish | sv |
|Danish | da |Hungarian | hu | Dutch | nl | Thai | th |
|German | de |Indonesian | id | Norwegian | no | Turkish | tr |
|English | en |Italian | it | Polish | pl | Ukrainian | uk |
|Spanish | es |Japanese | ja | Portuguese | pt | Vietnamese | vi |
|Finnish | fi |Korean | ko | Romanian | ro | Chinese | zh |
## Model Downloads
| Model Name | Description | Download |
| ----------- | ----------- |-----------
| 👉 **Seed-X-Instruct** | Instruction-tuned for alignment with user intent. |🤗 [Model](https://huggingface.co/ByteDance-Seed/Seed-X-Instruct-7B)|
| Seed-X-PPO | RL trained to boost translation capabilities. | 🤗 [Model](https://huggingface.co/ByteDance-Seed/Seed-X-PPO-7B)|
|Seed-X-RM | Reward model to evaluate the quality of translation.| 🤗 [Model](https://huggingface.co/ByteDance-Seed/Seed-X-RM-7B)|
## Quickstart
Here is a simple example demonstrating how to load the model and perform translation using ```vllm```
```python
from vllm import LLM, SamplingParams
model = LLM(model=model_path,
max_num_seqs=512,
tensor_parallel_size=8,
enable_prefix_caching=True,
gpu_memory_utilization=0.95)
messages = [
"Translate the following English sentence :\nMay the force be with you <zh>", # without CoT
"Translate the following English sentence and explain it in detail:\nMay the force be with you <zh>" # with CoT
]
results = model.generate(messages, decoding_params)
responses = [res.outputs[0].text.strip() for res in results]
print(responses)
```
## Evaluation
We evaluated Seed-X on a diverse set |