Arcee-ai
Models by this creator
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Llama-3.1-SuperNova-Lite
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Llama-3.1-SuperNova-Lite is an 8B parameter model developed by Arcee.ai, based on the Llama-3.1-8B-Instruct architecture. It is a distilled version of the larger Llama-3.1-405B-Instruct model, leveraging offline logits extracted from the 405B parameter variant. This 8B variation of Llama-3.1-SuperNova maintains high performance while offering exceptional instruction-following capabilities and domain-specific adaptability. The model was trained using a state-of-the-art distillation pipeline and an instruction dataset generated with EvolKit, ensuring accuracy and efficiency across a wide range of tasks. Llama-3.1-SuperNova-Lite excels in both benchmark performance and real-world applications, providing the power of large-scale models in a more compact, efficient form ideal for organizations seeking high performance with reduced resource requirements. Model inputs and outputs Inputs Text Outputs Text Capabilities Llama-3.1-SuperNova-Lite excels at a variety of text-to-text tasks, including instruction-following, open-ended question answering, and knowledge-intensive applications. The model's distilled architecture maintains the strong performance of its larger counterparts while being more resource-efficient. What can I use it for? The compact and powerful nature of Llama-3.1-SuperNova-Lite makes it an excellent choice for organizations looking to leverage the capabilities of large language models without the resource requirements. Potential use cases include chatbots, content generation, question-answering systems, and domain-specific applications that require high-performing text-to-text capabilities. Things to try Explore how Llama-3.1-SuperNova-Lite performs on your specific text-to-text tasks, such as generating coherent and informative responses to open-ended prompts, following complex instructions, or answering knowledge-intensive questions. The model's strong instruction-following abilities and domain-specific adaptability make it a versatile tool for a wide range of applications.
Updated 9/19/2024
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Arcee-Agent
79
Arcee-Agent is a cutting-edge 7B parameter language model specifically designed for function calling and tool use. Initialized from Qwen2-7B, it rivals the performance of much larger models while maintaining efficiency and speed. This model is particularly suited for developers, researchers, and businesses looking to implement sophisticated AI-driven solutions without the computational overhead of larger language models. Compared to similar models like Arcee-Spark, Arcee-Agent focuses more on advanced function calling capabilities, allowing it to seamlessly interact with a wide range of external tools, APIs, and services. It also supports multiple tool use formats, including Glaive FC v2, Salesforce, and Agent-FLAN, making it a versatile choice for diverse applications. Model Inputs and Outputs Arcee-Agent takes in text-based prompts and can generate text outputs, as well as execute external function calls. Inputs Text Prompts**: The model accepts text-based prompts that describe a task or request. Function Definitions**: At the start of a conversation, the model is provided with a definition of the available functions it can call to assist the user. Outputs Text Responses**: The model generates natural language responses to the user's prompts. Function Calls**: When appropriate, the model will output a structured function call, prefixed with ``, to execute an external tool or service. Capabilities Arcee-Agent excels at interpreting, executing, and chaining function calls, allowing it to seamlessly integrate with a wide range of external tools and services. This capability makes it well-suited for applications that require sophisticated AI-driven automation, such as: API Integration**: Easily interact with external APIs to fetch real-time data, post updates to social media, send emails, and more. Workflow Automation**: Chain multiple function calls together to automate complex multi-step workflows. Business Process Optimization**: Leverage Arcee-Agent's function calling abilities to streamline and optimize various business processes. What Can I Use It For? Developers, researchers, and businesses can leverage Arcee-Agent to build a wide range of AI-powered applications and solutions. Some potential use cases include: Intelligent Assistants**: Integrate Arcee-Agent into your virtual assistant to provide advanced functionality and seamless integration with external tools. Workflow Automation**: Automate complex workflows by chaining together function calls to external services and APIs. Business Process Optimization**: Use Arcee-Agent to analyze and optimize business processes, streamlining operations and improving efficiency. Rapid Prototyping**: Quickly develop and iterate on AI-powered features and products by leveraging Arcee-Agent's function calling capabilities. Things to Try One interesting aspect of Arcee-Agent is its dual-mode functionality, allowing it to serve as both an intelligent middleware for routing requests to appropriate tools and a standalone chat agent capable of engaging in human-like conversations. Consider experimenting with these different modes to see how the model can best suit your needs. Additionally, the model's support for various tool use formats, such as Glaive FC v2 and Salesforce, opens up a world of possibilities for integrating it into your existing technology stack. Try testing the model with different function definitions and observing how it adapts and responds.
Updated 8/7/2024
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Arcee-Spark
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The Arcee-Spark is a powerful 7B parameter language model that punches well above its weight class. Initialized from the Qwen2 model, it underwent a sophisticated training process including fine-tuning on 1.8 million samples, merging with the Qwen2-7B-Instruct model using Arcee's mergekit, and further refinement through Direct Preference Optimization (DPO). This meticulous process results in exceptional performance, with Arcee-Spark achieving the highest score on MT-Bench for models of its size and outperforming even GPT-3.5 on many tasks. Model inputs and outputs Inputs Text prompts**: Arcee-Spark is a text-to-text model that can generate output based on text inputs. Outputs Generated text**: The model can produce coherent and contextually relevant text in response to the input prompts. Capabilities Despite its compact 7B size, Arcee-Spark offers deep reasoning capabilities, making it suitable for a wide range of complex tasks. It demonstrates exceptional performance in areas such as advanced text generation, detailed question answering, and nuanced sentiment analysis. What can I use it for? Arcee-Spark offers a compelling solution for businesses looking to leverage advanced AI capabilities without the hefty computational requirements of larger models. Its unique combination of small size and high performance makes it ideal for real-time applications like chatbots and customer service automation, edge computing scenarios, cost-effective scaling of language AI across an organization, rapid prototyping of AI-powered features, and on-premise deployments that prioritize data privacy and security. Things to try While Arcee-Spark is already a highly capable model, its advanced training process allows it to deliver exceptional speed and efficiency compared to larger language models. Businesses can leverage these strengths to implement sophisticated AI-powered features and products without breaking the bank on infrastructure or API costs, making it an attractive choice for a wide range of use cases.
Updated 7/31/2024