{"id":183998,"date":"2024-03-28T12:11:59","date_gmt":"2024-03-28T11:11:59","guid":{"rendered":"https:\/\/liora.io\/en\/?p=183998"},"modified":"2026-08-07T10:22:15","modified_gmt":"2026-08-07T09:22:15","slug":"meta-goes-head-to-head-with-openai-and-gpt-4","status":"publish","type":"post","link":"https:\/\/liora.io\/en\/meta-goes-head-to-head-with-openai-and-gpt-4","title":{"rendered":"Meta goes head to head with OpenAI and GPT-4"},"content":{"rendered":"\n

Meta recently unveiled Code Llama-70B, an advanced version of its specialised language model for software development. With performance equivalent to or even better than GPT-4, this open source model goes head to head with the dominant model on the market.<\/strong><\/p>\n\n\n

Code Llama-70B an advanced version?<\/h2>\n\n\n

At the end of summer 2023, Meta announced Code Llama, an LLM<\/a> for software development. Code Llama now comes in four versions: 7, 13, 34 and now 70 billion parameters.<\/p>\n\n\n

Driven by 500 billion tokens, the first three models of Code Llama remain powerful, fast tools that are better suited to small configurations.<\/p>\n\n\n

7B is capable of running on a single GPU<\/a>. For its part, 70B has been trained with 1,000 billion tokens, and is presented by Meta as the perfect development assistant.<\/p>\n\n\n

As well as 70B, Meta is also promoting two versions of Code Llama: Code Llama Python and Code Llama Instruct, in all possible versions (7, 13, 34 and 70). All these models are derived from Llama 2 and hosted by Hugging Face.<\/a><\/p>\n\n\n

\"Illustration<\/figure>\n\n\n
Learn how to use LLM<\/a><\/div><\/div>\n\n\n

What are the advantages of Code Llama Python and Instruct?\n<\/h2>\n\n\n

Code Llama Python is optimised for a wide variety of programming tasks, including web scraping, data analysis and web development. Its versatility and performance make it a valuable tool for code generation.<\/p>\n\n\n

Code Llama Instruct can perform numerous tasks and manipulations in natural language. Its capabilities include filtering, searching, sorting and manipulating data, as well as binary and factorial searching.<\/p>\n\n\n

\"Illustration<\/figure>\n\n\n

Llama-70B code more powerful than GPT-4?<\/h2>\n\n\n

To make its case, Meta says it has had its new model tested with HumanEval and Mostly Basic Python Programming (MBPP)<\/strong>. HumanEval tests the model’s ability to complete code, while MBPP evaluates the model’s ability to write code based on a description.<\/p>\n\n\n

As a result, Instruct 70B achieved a score of 67.8% on HumanEval, compared with 67% for GPT-4. Python 70B beat Llama 70B’s previous record of 62.4% to score 65.6%. These new records make Llama the most powerful open source LLM on the market.<\/p>\n\n\n

\"Illustration<\/figure>\n\n\n

If you’ve enjoyed this article, and you’re considering a career in Data Science or simply want to improve your skills in your field, don’t hesitate to check out our training offers or our blog articles on Liora.<\/p>\n\n\n

Source : ai.meta.com<\/p>\n\n\n

Discover our training in artificial intelligence<\/a><\/div><\/div>\n\n","protected":false},"excerpt":{"rendered":"

Meta recently unveiled Code Llama-70B, an advanced version of its specialised language model for software development. With performance equivalent to or even better than GPT-4, this open source model goes head to head with the dominant model on the market. Code Llama-70B an advanced version? At the end of summer 2023, Meta announced Code Llama, […]<\/p>\n","protected":false},"author":76,"featured_media":184000,"comment_status":"open","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"_acf_changed":false,"editor_notices":[],"footnotes":""},"categories":[2433],"class_list":["post-183998","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-ai"],"acf":[],"_links":{"self":[{"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/posts\/183998","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/users\/76"}],"replies":[{"embeddable":true,"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/comments?post=183998"}],"version-history":[{"count":3,"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/posts\/183998\/revisions"}],"predecessor-version":[{"id":209718,"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/posts\/183998\/revisions\/209718"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/media\/184000"}],"wp:attachment":[{"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/media?parent=183998"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/liora.io\/en\/wp-json\/wp\/v2\/categories?post=183998"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}