In a groundbreaking move, Meta has today officially launched Code Llama, a revolutionary family of large language models designed to help you write programs and code. This innovative tool, based on the Llama 2 model, is set to redefine the coding landscape with its state-of-the-art performance, infilling capabilities, and support for large input contexts. What sets Code Llama apart is its zero-shot instruction following ability for programming tasks, a feature that is sure to be a game-changer for developers worldwide.
Code Llama comes in multiple flavors to cater to a broad spectrum of applications. The foundation models, known as Code Llama, are designed to be versatile and adaptable. For Python enthusiasts, there are Python specializations, aptly named Code Llama – Python. The instruction-following models, Code Llama – Instruct, are designed with 7B, 13B, and 34B parameters each, offering a range of options for users.
All models are trained on sequences of 16k tokens and have shown significant improvements on inputs with up to 100k tokens. The 7B and 13B Code Llama and Code Llama – Instruct variants have the added advantage of supporting infilling based on surrounding content.
Code Llama AI coding tool
Code Llama’s performance is nothing short of impressive. It has achieved state-of-the-art performance among open models on several code benchmarks, scoring up to 53% and 55% on HumanEval and MBPP, respectively. Notably, Code Llama – Python 7B has outperformed Llama 2 70B on HumanEval and MBPP. All models have outperformed every other publicly available model on MultiPL-E, a testament to their superior design and functionality.
Test out Code Llama now
For those eager to test out Code Llama, the good news is that it is now available via the Perplexity AI Labs website. Users can interact with Code Llama through a web interface, where they can ask questions and see how the model responds.
The Python model was further trained on more tokens and broken out into three different sizes: 7B, 13B, and 34B. This unique approach involved generating 62,000 interview-style programming questions from prompting Llama 270b, removing duplicates, generating unit tests, and then generating 10 solutions. The first solution that passed the test was added to the dataset.
Code Llama’s performance has been exceptional, even surpassing some models of GPT 3.5 in certain metrics. This new large language model is capable of generating code and natural language about code, making it a powerful tool for developers and programmers.
Code Llama is not just a new coding tool; it’s a game-changer. With its unique features and impressive performance, it’s set to revolutionize the way we approach coding. Whether you’re a seasoned developer or a coding novice, Code Llama is a tool worth exploring.
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Specialized version of Llama 2
Code Llama is an advanced, code-specialized variant of the state-of-the-art language model, Llama 2. It was developed by extending the training of Llama 2 on its code-specific datasets. Through rigorous and extensive sampling from this rich dataset over an extended period, Code Llama has been engineered with a core focus in managing and deciphering code.
Imbued with robust coding capabilities, Code Llama is not merely an upgrade but a significant enhancement over Llama 2’s features. Its special attributes are exhibited in its ability to generate code along with the corresponding natural language conversation about the code. This groundbreaking attribute sets new standards in the realm of coding, enabling an intuitive understanding of the context and purpose of the code. Furthermore, this proficiency extends to interpreting and handling both code-based and natural language prompts. For example, if provided with a command such as “Write me a function that outputs the fibonacci sequence,” Code Llama is designed to effortlessly comply, producing the necessary lines of code.
Code Llama also serves as a versatile tool for code completion and debugging. It is capable of comprehending incomplete codes or structures, offering the potential to complete them efficiently. Additionally, should any bugs be present in the code, Code Llama’s advanced algorithm allows it to detect and highlight them, thereby simplifying the bug-fixing process.
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