Code Llama: Empowering Developers with the Power of AI — Part 1 (Intro)

Meta's Code Llama represents a significant advancement in large language models (LLMs), specifically tailored for the realm of software development. This open-source tool leverages cutting-edge AI technology to assist developers of all levels in streamlining their workflows, enhancing code quality, and fostering deeper understanding. In this two part series, we’ll first introduce Code Llama, then show you how to use it i your own coding workflow, both directly and by adding it to an IDE.

Capabilities:

• Code Generation: CodeLlama can generate complete code snippets, functions, or even entire programs based on user-provided instructions and contextual information. This empowers developers to automate repetitive tasks and focus on more strategic aspects of development.
• Code Completion: The model excels at suggesting relevant code completions, significantly reducing development time and effort. This fosters a more fluid and efficient coding experience for users.
• Code Infilling: Given partial code blocks, CodeLlama can effectively "fill in the blanks" to create a functional whole. This proves invaluable for addressing incomplete code or repairing existing structures.
• Bug Identification and Correction: CodeLlama possesses the ability to identify potential bugs within code and recommend corresponding fixes. This proactive approach aids in mitigating errors and promoting robust software creation.
• Code Comprehension and Explanation: The model can analyze code and provide clear explanations of its functionality. This fosters a deeper understanding of underlying code structures and their intended purpose.

Target Audience:

• Professional Developers: CodeLlama serves as a valuable tool for professional developers, regardless of their experience level. By accelerating development processes, enhancing code quality, and providing deeper code insights, the model significantly impacts productivity and overall workflow efficiency.
• Beginner Developers: Those new to the coding world can leverage CodeLlama's capabilities to learn and grow faster. The model's code completion and explanation features offer valuable support in understanding code structures and best practices.
• Researchers and Educators: CodeLlama presents a unique platform for exploring the applications of AI in software development. Researchers can leverage the model for experimentation and advancement in the field, while educators can utilize it to enrich their curriculum and provide students with an invaluable learning tool.

Technical Prowess:

• Surpasses GPT-4 in coding tasks: While both are LLMs, CodeLlama's 70 billion parameter model, Code LLaMA 70b, specifically targets coding and outperforms GPT-4 in this domain.
• Open-source and accessible: Unlike many other powerful AI models, CodeLlama's code and models are readily available for anyone to explore and experiment with, fostering innovation and collaboration.
• Hugging Face compatibility: Its integration with the popular Hugging Face Transformers library makes it easily accessible to a wider developer community, reducing integration hurdles.

Next, let’s look at how you can simply play with the model if you do not want to delve deeply or if you are not a developer at all, and after that I will tell you how you can directly use this model in the development environment for everyday tasks.

Let’s play first

To simplify getting to know Code Llama, we will simply use the already deployed Spaces on the Hugging Face. There are two official spaces: Code Llama Playground and Code Llama 13B Chat. Let’s review them.

Keep in mind that the model’s responses can differ even for the same input!

Code Llama Playground is based on the codellama/CodeLlama-13b-hf model and is not designed for instruction purposes but for code completion, which means that most often it will respond with dry code examples.

Let’s ask it to <code>WriteJavaScript code that sorts these numbers: 7 1 3 9 0 2 5 4 8 6</code>

The response will be:

### Solution

```javascript
function sortNumbers(arr) {
 // change code below this line
 arr.sort((a, b) => a - b);
 // change code above this line
}
const numbers = [7, 1, 3, 9, 0, 2, 5, 4, 8, 6];
console.log(numbers); // should be [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
```

Or,  we can do the same for Python: <code>Write a code example in Python that sorts these numbers: 7 1 3 9 0 2 5 4 8 6,</code> and the model responds with:

Write a code example in Python that sorts these numbers: 7 1 3 9 0 2 5 4 8 6

# 1.
numbers = [7, 1, 3, 9, 0, 2, 5, 4, 8, 6]
print(sorted(numbers))

# 2.
numbers = [7, 1, 3, 9, 0, 2, 5, 4, 8, 6]
numbers.sort()
print(numbers)

# 3.
numbers = [7, 1, 3, 9, 0, 2, 5, 4, 8, 6]
numbers.sort(reverse=True
)print(numbers)

# 4.
numbers = [7, 1, 3, 9, 0, 2, 5, 4, 8, 6]
numbers.sort(key=lambda x: -x)
print(numbers)

Or … <code>Write Java code that sorts the elements of an array</code> and the response is:

Write Java code that sorts the elements of an array.

```java
public class ArraySort {
    public static void main(String[] args) {
        int[] arr = { 1, 2, 3, 4, 5 };
        for (int i = 0; i < arr.length - 1; i++) {
            for (int j = i + 1; j < arr.length; j++) {
                if (arr[i] > arr[j]) {
                    int temp = arr[i];
                    arr[i] = arr[j];
                    arr[j] = temp;
                }
            }
        }
        System.out.println("Sorted array: ");
        for (int i = 0; i < arr.length; i++) {
            System.out.print(arr[i] + " ");
        }
    }
}
```

### Output

```
Sorted array: 
1 2 3 4 5
```

The second space, Code Llama 13B Chat, demonstrates the CodeLlama-13b-Instruct model, a Code Llama model with 13B parameters fine-tuned for chat instructions and specialized on code tasks. This model will describe its responses with more detail. Let’s put the same inputs in this space:

Input: <code>Write JavaScript code that sorts these numbers: 7 1 3 9 0 2 5 4 8 6</code>

Output:

Here is a JavaScript function that sorts the given numbers in ascending order:

function sortNumbers(numbers) {
 return numbers.sort((a, b) => a - b);
}

console.log(sortNumbers([7, 1, 3, 9, 0, 2, 5, 4, 8, 6]));

This function uses the sort() method to sort the array of numbers in ascending order. The sort() method takes a callback function as an argument, which is used to compare the elements of the array. In this case, the callback function is (a, b) => a - b, which subtracts the first element from the second element. This causes the array to be sorted in ascending order.

The console.log() statement is used to print the sorted array to the console.

Note that this function assumes that the input array is an array of numbers. If the input array is not an array of numbers, the function will throw an error.

Input:  <code>Write Java code that sorts the elements of an array</code>

Output:

Here is Java code that sorts the elements of an array:

public class ArraySort {
 public static void main(String[] args) {
   int[] arr = {3, 2, 1, 4, 5};
   Arrays.sort(arr);
   System.out.println(Arrays.toString(arr));
 }
}

This code sorts the elements of the array arr using the Arrays.sort() method. The Arrays.toString() method is used to print the sorted array to the console.

Note: This code assumes that the array arr is an array of integers. If the array is not an array of integers, you will need to modify the code accordingly.

The ability to play with the model in these spaces enables you to get acquainted with the model's capabilities without the need for complex setup and installation on your computer.

In addition, the source code of each space is open and you can see how they are configured and see how to connect to the HF instance in the same way:

More on this later.

But now it’s time to dive deeper.  Stay tuned for part 2!