codegemma:2b-code-q5_0

智能代码补全和生成：完成行、函数，甚至生成整个代码块，无论您是在本地工作还是使用 Google Cloud 资源。
增强的准确性：CodeGemma 模型在主要来自网络文档、数学和代码的 5000 亿个 token 的英语数据上进行训练，生成的代码不仅在语法上更正确，而且在语义上更有意义，从而减少错误和调试时间。
多语言熟练度：支持 Python、JavaScript、Java、Kotlin、C++、C#、Rust、Go 和其他语言。
简化的工作流程：将 CodeGemma 模型集成到您的开发环境中，以减少编写样板代码，并更快地专注于重要的、有趣的且与众不同的代码。

中间填充

CodeGemma 模型支持中间填充 (FIM)，用于自动完成或编码助手工具。以下是使用 Ollama Python 库的示例。

response = generate(
  model='codegemma:2b-code',
  prompt=f'<|fim_prefix|>{prefix}<|fim_suffix|>{suffix}<|fim_middle|>',
  options={
    'num_predict': 128,
    'temperature': 0,
    'top_p': 0.9,
    'stop': ['<|file_separator|>'],
  },
)

参考

Hugging Face

报告

CodeGemma is a collection of powerful, lightweight models that can perform a variety of coding tasks like fill-in-the-middle code completion, code generation, natural language understanding, mathematical reasoning, and instruction following.

### Variants:

* `instruct` a 7b instruction-tuned variant for natural language-to-code chat and instruction following
* `code` a 7b pretrained variant that specializes in code completion and generation from code prefixes and/or suffixes
* `2b` a state of the art 2B pretrained variant that provides up to 2x faster code completion

### Advantages:

* **Intelligent code completion and generation**: Complete lines, functions, and even generate entire blocks of code, whether you're working locally or using Google Cloud resources.

* **Enhanced accuracy**: Trained on 500 billion tokens of primarily English language data from web documents, mathematics, and code, CodeGemma models generate code that's not only more syntactically correct but also semantically meaningful, reducing errors and debugging time.

* **Multi-language proficiency**: Supports Python, JavaScript, Java, Kotlin, C++, C#, Rust, Go, and other languages.

* **Streamlined workflows**: Integrate a CodeGemma model into your development environment to write less boilerplate and focus on interesting and differentiated code that matters, faster.

![benchmarks](https://github.com/ollama/ollama/assets/251292/0d8473cb-bcee-4bd0-9214-c527ce367d88)

### Fill-in-the-middle

CodeGemma models support fill-in-the-middle (FIM), for use in autocomplete or coding assistant tooling. Below is an example using the Ollama [Python](https://github.com/ollama/ollama-python) library:

```python
response = generate(
  model='codegemma:2b-code',
  prompt=f'<|fim_prefix|>{prefix}<|fim_suffix|>{suffix}<|fim_middle|>',
  options={
    'num_predict': 128,
    'temperature': 0,
    'top_p': 0.9,
    'stop': ['<|file_separator|>'],
  },
)
```

### References

[Hugging Face](http://hugging-face.cn/collections/google/codegemma-release-66152ac7b683e2667abdee11)

[Report](https://storage.googleapis.com/deepmind-media/gemma/codegemma_report.pdf)

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