chinese

**Multilingual LLMs (中英双语)** **Models Optimized for Chinese** **Chinese-First Models** | Model | Provider | Parameters | Highlights | |-------|----------|------------|------------| | Qwen 2 | Alibaba | 7B-72B | Best Chinese open model | | ChatGLM | Zhipu AI | 6B-130B | Native Chinese architecture | | Baichuan | Baichuan | 7B-53B | Strong bilingual | | DeepSeek | DeepSeek | 7B-67B | Code + Chinese | | Yi | 01.AI | 6B-34B | Strong reasoning | **Multilingual Commercial Models** | Model | Chinese Quality | Notes | |-------|-----------------|-------| | GPT-4 | Excellent | 100+ languages | | Claude 3 | Very Good | Strong for translation | | Gemini | Very Good | Google multilingual | **Translation Best Practices** **Prompt Template for Translation** ``` You are a professional translator specializing in {domain}. Translate the following from {source_lang} to {target_lang}. Preserve the original meaning, tone, and formatting. Source text: {text} Translation: ``` **Common Issues and Solutions** | Issue | Solution | |-------|----------| | Literal translation | Add "natural and fluent" instruction | | Lost idioms | "Adapt idioms to equivalent expressions" | | Wrong formality | Specify formal/informal register | | Technical terms | Provide glossary in prompt | **Tips for Chinese-English Tasks** **Handling Mixed Text** ```python **For code with Chinese comments** prompt = """ Translate ONLY the Chinese comments to English. Keep all code unchanged. ```python **这是一个计算函数** def calculate(x, y): return x + y # 返回结果 ``` """ ``` **Tokenization Efficiency** Chinese text typically uses 2-3x more tokens than English: - "人工智能" (4 characters) ≈ 3 tokens - "Artificial Intelligence" (25 characters) ≈ 3 tokens Consider this for cost estimation. **Evaluation for Chinese** | Benchmark | Description | |-----------|-------------| | C-Eval | Chinese multitask evaluation | | CMMLU | Chinese massive multitask | | CLUE | Chinese Language Understanding | | SuperCLUE | Advanced Chinese benchmark | **Code Example** ```python from openai import OpenAI client = OpenAI() response = client.chat.completions.create( model="gpt-4", messages=[ {"role": "system", "content": "你是一位专业的中英翻译。"}, {"role": "user", "content": "请将以下文字翻译成英文:半导体制造需要极高的精度。"} ] ) print(response.choices[0].message.content) **Output: "Semiconductor manufacturing requires extremely high precision."** ```

Go deeper with CFSGPT

Get AI-powered deep-dives, save terms, and run advanced simulations — free account.

Create Free Account