Introducing Code Llama An AI Solution For Programming Assistance

Introducing Code Llama An AI Solution For Programming Assistance

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Table Of Contents

  • Introduction
  • Introducing Code Llama, an AI solution for programming assistance
  • Different Sizes Of Code Llama
  • Evaluating Code Llama’s performance
  • Summary
  • References

Introduction

Introducing Code Llama, an AI solution for programming assistance. Which is just released by the Meta (Facebook) and it is open source.

What is Code Llama?

  • Code Llama is an AI model built on top of Llama 2 and fine-tuned for generating and discussing code.
  • It’s free for research and commercial use.
  • Built upon Llama 2, Code Llama is accessible through three models:
    • Code Llama, the foundational code model;
    • Codel Llama – Python specialized for Python;
    • Code Llama – Instruct, on the other hand, undergoes fine-tuning to excel at comprehending natural language instructions.

Code Llama Github URL:

Introducing Code Llama An AI Solution For Programming Assistance

Facebook (Meta) is unveiling Code Llama, a powerful language model (LLM) capable of using text prompts to generate code and engage in code-related discussions.

Code Llama represents the cutting edge among publicly accessible LLMs for coding tasks.

Its potential lies in streamlining developer workflows, enhancing efficiency, and reducing barriers for coding novices.

As a productivity and educational aide, Code Llama holds promise in assisting programmers to create more robust and well-documented software.

Their approach to AI prioritizes openness, innovation, safety, and responsibility. Consequently, they are making Code Llama available for both research and commercial applications under the same community license as Llama 2.

Different Sizes Of Code Llama

Code Llama SizesParametersTraining TokensAdditional Capabilities
7B7 billion500 billionFIM (Fill-in-the-middle) for code completion
13B13 billion500 billionFIM (Fill-in-the-middle) for code completion
34B34 billion500 billion

Explanation:

  • Code Llama Sizes: Refers to the different versions of Code Llama available.
  • Parameters: Indicates the number of parameters used in the respective model.
  • Training Tokens: Denotes the quantity of code and code-related data tokens used for training.
  • Additional Capabilities: Highlights the extra functionality of the 7B and 13B models, featuring Fill-in-the-middle (FIM) capability for tasks like code completion right from the start. The 34B model’s additional capabilities aren’t specified in this context.

Evaluating Code Llama’s performance

In this post, we Introduce Code Llama, an AI solution for programming assistance. Which is just released by the Meta (Facebook) and it is open source.

As with all cutting-edge technology, Code Llama comes with risks. Building AI models responsibly is crucial, and they undertook numerous safety measures before releasing Code Llama.

As part of their red teaming efforts, they ran a quantitative evaluation of Code Llama’s risk of generating malicious code.

They created prompts that attempted to solicit malicious code with clear intent and scored Code Llama’s responses to those prompts against ChatGPT’s (GPT3.5 Turbo). Their results found that Code Llama answered with safer responses.

Download Llama Models :

Summary

However, it’s crucial to recognize that utilizing Code Llama or Code Llama – Python for general natural language tasks is not recommended, given that these models aren’t designed to comply with natural language instructions.

Code Llama retains its specialization for code-specific tasks and is not meant to serve as a foundational model for other objectives.

For more information and learning,

References

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