xLAM-7b-fc-r
Maintainer: Salesforce
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
The xLAM-7b-fc-r model is part of the xLAM model family developed by Salesforce. xLAMs are advanced large language models designed to enhance decision-making and translate user intentions into executable actions that interact with the world. The xLAM-7b-fc-r model is optimized for function-calling capability, providing fast, accurate, and structured responses based on input queries and available APIs. This model is fine-tuned based on the deepseek-coder models and is designed to be small enough for deployment on personal devices.
The model series also includes the xLAM-1b-fc-r and xLAM-7b-fc-r versions, which vary in size and context length to cater to different applications. These models are part of the broader LAM (Large Action Model) family, which aims to serve as the "brains" of AI agents by autonomously planning and executing tasks to achieve specific goals.
Model inputs and outputs
Inputs
- Natural language queries: The model can accept a wide range of natural language inputs, from simple questions to complex instructions, which it then translates into executable actions.
- Available APIs: The model can utilize information about available APIs and services to generate appropriate responses and actions.
Outputs
- Structured responses: The model provides detailed, step-by-step responses that outline the actions to be taken, often in a format that can be directly integrated with external systems or applications.
- Executable actions: Beyond just generating text, the model can produce executable actions, such as API calls, that can be directly integrated into workflow processes.
Capabilities
The xLAM-7b-fc-r model excels at translating user intentions into executable actions, enabling the automation of various workflow processes. For example, it can assist with tasks like scheduling appointments, managing to-do lists, or even programming simple APIs - all through natural language interactions. The model's function-calling capabilities make it particularly useful for enhancing productivity and streamlining operations across a wide range of domains.
What can I use it for?
The xLAM-7b-fc-r model and the broader xLAM series have numerous applications, including:
- Workflow automation: Integrate the model into business processes to automate repetitive tasks and enhance productivity.
- Personal digital assistants: Leverage the model's natural language understanding and action-generation capabilities to build intelligent virtual assistants.
- No-code/low-code development: Utilize the model's function-calling abilities to enable non-technical users to create custom applications and integrations.
- Intelligent process automation: Combine the model's decision-making and action-planning skills with robotic process automation (RPA) for end-to-end workflow optimization.
Things to try
One interesting aspect of the xLAM-7b-fc-r model is its ability to handle multi-step tasks and break them down into structured, executable steps. Try providing the model with complex instructions or a series of related queries, and observe how it plans and responds to achieve the desired outcome. The model's versatility in translating natural language into effective actions makes it a powerful tool for streamlining various workflows and automating repetitive processes.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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