What's new? (June 2024)
For Tabnine's private installation release notes, click here.
June 27, 2024
Anthropic's Claude 3.5 Sonnet is now available on Tabnine Chat
In keeping with our goal of supporting the latest and most advanced models, we’ve recently updated our support for Anthropic’s models with the switch to Claude 3.5 Sonnet. As with all of the other models Tabnine supports, you are now able to use the Claude 3.5 Sonnet model with any chat interactions with Tabnine, including software planning (i.e., asking general coding questions or better understanding code in an existing project), code generation, code explanation, and project onboarding, creating tests, fixing code, creating documentation, and refactoring code.
June 21, 2024
Version 5.7.0 is here!
Version 5.7.0 of Tabnine's private installation is live, with updated usage reporting.
June 20, 2024
Cohere's Command R is now available on Tabnine Chat
We’re excited to announce that the Cohere Command R model is now available as one of the underlying LLMs that powers Tabnine Chat. Tabnine is partnering with Cohere, the enterprise-focused AI platform to bring the Command R model to Tabnine. You get the full capability of Tabnine’s AI chat with the Command R model — including code generation, code explanations, documentation generation, and AI-created tests — as well as highly personalized recommendations by utilizing the context from locally available data in your IDE and your organization’s global codebases.
June 5, 2024
Anthropic's Claude 3 Sonnet is now available on Tabnine Chat
We’re thrilled to announce that Tabnine is partnering with Anthropic, the leading AI research and safety company to make the Claude 3 Sonnet model available as one of the underlying LLMs that powers Tabnine Chat. You get the full capability of Tabnine Chat with the Claude 3 Sonnet model including code generation, code explanations, documentation generation, AI-created tests, and more. Additionally, when using the Claude 3 Sonnet model, Tabnine Chat delivers highly personalized recommendations by utilizing the context from locally available data in your IDE as well as your organization’s global codebases.
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