Rubra
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About
Rubra is a collection of open-weight large language models (LLMs) that enhances their functionality by integrating tool-calling capabilities. This allows the models to execute user-defined external tools deterministically while reasoning and conversing, making them suitable for complex tasks. Enhanced with post-training methods to teach new skills without catastrophic forgetting, Rubra models are designed for ease of use, supporting popular inferencing tools for local implementations. Users can access a variety of enhanced models with different sizes and context lengths, such as Meta-Llama and Mistral, and conduct demos without any setup through Hugging Face Spaces.
Platform
Features
• open-source models
• tool-calling capability
• available for local and cloud use
• enhanced from top llms
• supports complex function chaining
FAQs
Who are the intended users of Rubra?
Rubra models are for anyone looking to use open source LLMs with native function calling support, resulting in superior performance.
Why use Rubra models over alternatives?
Rubra excels at complex, multi-step function calls, enhancing popular instruct LLMs while maintaining their core capabilities.
How were Rubra models trained?
Rubra models were trained using a curated dataset of over 1 million conversations, utilizing extensive GPU resources.
Why do benchmark results vary from parent models?
Differences arise due to evolving tools used in benchmarking, but Rubra's results generally align with parent models.
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