IBM launches Granite: open-source AI that outperforms Meta models
Posted: Mon Jan 20, 2025 9:20 am
IBM has just announced a major development that promises to revolutionize programming: the launch of Granite, a new family of open-source artificial intelligence (AI). The main goal of this innovation is to make life easier for developers in various sectors by simplifying coding processes.
Features and availability
Granite language models address common challenges in software development. They simplify tasks such as writing, testing, debugging, and shipping code efficiently and reliably. They are also available on popular platforms such as Hugging el salvador phone number library Face, GitHub, watsonx.ai, and RHEL AI.
Distributed under the Apache 2.0 license, these templates promote broad accessibility. Thus, they facilitate collaboration within the developer community.
Granite's superior performance and flexibility
According to Analytics India Magazine, IBM has released four variations of Granite, with parameters ranging from 3 billion to 34 billion. This diversity allows the models to adapt to different database requirements and complexity.
Furthermore, extensive testing on various benchmarks demonstrated the superiority of these models over others on the market, such as Code Llama and Llama 3. They particularly excelled in code synthesis, correction and translation tasks in major programming languages, including Python, JavaScript and Java.
Features and availability
Granite language models address common challenges in software development. They simplify tasks such as writing, testing, debugging, and shipping code efficiently and reliably. They are also available on popular platforms such as Hugging el salvador phone number library Face, GitHub, watsonx.ai, and RHEL AI.
Distributed under the Apache 2.0 license, these templates promote broad accessibility. Thus, they facilitate collaboration within the developer community.
Granite's superior performance and flexibility
According to Analytics India Magazine, IBM has released four variations of Granite, with parameters ranging from 3 billion to 34 billion. This diversity allows the models to adapt to different database requirements and complexity.
Furthermore, extensive testing on various benchmarks demonstrated the superiority of these models over others on the market, such as Code Llama and Llama 3. They particularly excelled in code synthesis, correction and translation tasks in major programming languages, including Python, JavaScript and Java.