Introduction
Everyone online is talking about Meta's new AI model, Code Lama, and it's easy to see why. It's an impressive tool that can create and talk about code through text prompts. Code Lama is more advanced than any tool we've known. In this article, I'll explain all the details about Code Lama, its features, how it stands out from other AI tools, and ways you can start using it today.
What is Code Lama?
According to Meta's blog post, Code Lama is a large language model that is fine-tuned for coding tasks. It's built on top of Llama 2, which is Meta's general-purpose language model that can handle text, images, and other modalities. Code Lama is specialized for generating and discussing code from both code and natural language prompts.
For example, you can ask Code Lama to write a function that outputs the Fibonacci sequence or explain what a piece of code does. It can also help you with code completion and debugging by inserting code into existing scripts or finding errors in your code.
Code Lama supports many popular programming languages used today, such as Python, C++, Java, PHP, TypeScript, Bash, and more. It can handle up to 100,000 tokens of context, which means it can work with large and complex code bases. This is a huge improvement over many existing models that can only handle a few thousand tokens at most.
Size and Training of Code Lama
Meta has released three sizes of Code Lama: 7B, 13B, and 34B parameters. Each of these models has been trained with 500 billion tokens of code and code-related data. The bigger the model, the better the results, but also the slower the speed.
The 7B model can be served on a single GPU, while the 34B model requires a supercomputer. The 13B model is somewhere in between. Meta has also created two additional variations of Code Lama: Code Lama Python and Code Lama Instruct.
Code Lama Python is a model that is further fine-tuned on Python code only, making it more suitable for Python developers and learners. Python is one of the most widely used and benchmarked languages for coding. Code Lama Instruct is a model that is fine-tuned for understanding natural language instructions better. So when you ask it to do something in simple words, it can figure out what you mean and produce the right code for you.
Unique Features of Code Lama
One of the coolest features of Code Lama is its Fill in the Middle (FIM) capability. It lets you add code into what you've already written without removing or replacing any of it. This is great when you need to finish a part of your code without changing everything else. For example, if you made a function to add two numbers but forgot to put in the part that gives back the result, you can get Code Lama to finish that part for you with FIM.
Comparison to Competitors
The main competitors to Code Lama are Chat GPT and GitHub Co-pilot Chat. Chat GPT is based on the GPT 3.5 model, and GitHub Co-pilot Chat uses the Codex for context. Codex is a large language model from OpenAI trained using code from GitHub.
While both Chat GPT and GitHub Co-pilot Chat are great at generating and discussing code when given text instructions, they have some limitations. They can only manage up to 2048 tokens of context, so they might struggle with large or complicated coding projects. They can also sometimes make mistakes in accuracy and produce code that's not entirely safe or correct.
In various tests, Code Lama performs better than both competitors. In the human Evil test developed by OpenAI to see how well a program can write code based on written descriptions called doc strings, Code Lama solves 28.8 percent of the problems, while Chat GPT solves 0 percent and GitHub Co-pilot Chat solves 11.4 percent.
Code Lama is also more likely to produce factual and safe responses than Chat GPT and GitHub Co-pilot Chat, as it has been aligned using more human feedback and adversarial testing.
Comparison to GPT4
Although GPT4 has some advantages over Code Lama, such as handling visual input and generating more creative and collaborative content, it is not specialized for coding tasks. On the human Evil test, GPT4 only solves 18.6 percent of the problems, while Code Lama solves 28.8 percent. Code Lama also has features that GPT4 does not have, such as FIM capability and instruction fine-tuning.
Unnatural Code Lama
Meta is working on an upcoming version of Code Lama called Unnatural Code Lama. It has been trained on a secret data set of unnatural code, which is deliberately written in a way that violates coding conventions or best practices. This makes the model more robust and adaptable to different coding styles and scenarios. Unnatural code can also be used as a form of obfuscation or encryption to make the code harder to read or reverse engineer.
Although Unnatural Code Lama is still in development, leaked results have shown that it can rival GPT4's performance on various benchmarks. It can pass a simulated bar exam with a score around the top 10 percent of test takers and generate code that is indistinguishable from human-written code by experts.
Availability and Implementation
If you want to get your hands on Code Lama, it is now available via the Perplexity AI Labs website, where you can interact with it through a web interface. You can also try the Code Lama model 13B in the Code Lama Playground on Hugging Face.
One advantage of using Code Lama over GPT4 is its accessibility and implementation. Code Lama can run on local machines, while GPT4 requires cloud-based servers. Additionally, Code Lama does not have any subscription models or usage limits. You can use Code Lama as much as you want without paying anything extra or being restricted by quotas or tiers. You also don't have to worry about potential ethical or legal concerns that might arise from using GPT4's cloud-based mechanism.
Potential and Future Implications
Code Lama is a game changer for coders of all levels and domains. It helps you write and understand code quickly, learn new coding techniques, and discuss code with others. However, it's not flawless. It might struggle with unique cases or new programming languages and may face legal issues, such as code that breaks copyright rules.
There are also competition tools like GPT4 or others optimized for specific coding tasks that might challenge Code Lama. To stay relevant, Code Lama needs to keep evolving. Meta is already working on updates like Unnatural Code Lama and adding image input.
Conclusion
Meta's Code Lama is an impressive AI model that revolutionizes the way we interact with code. It's more advanced than any other tool in the market and has several unique features that set it apart from its competitors. With its ability to generate and discuss code, Code Lama is a valuable asset for coders of all skill levels. Whether you're a beginner or an expert, Code Lama can help you write code faster and more efficiently.
While Code Lama is not perfect and may face challenges in the future, it's a significant step forward in AI programming. Its availability, accessibility, and implementation make it a practical choice for developers. As Meta continues to improve and expand Code Lama's capabilities, we can expect even more exciting developments in the field of AI programming.
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