nguyenthanhthuan/Llama_3.2_1B_Intruct_Tool_Calling_V2

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:1BQuant:BF16Ctx Length:32kPublished:Oct 28, 2024License:apache-2.0Architecture:Transformer0.0K Open Weights Warm

The nguyenthanhthuan/Llama_3.2_1B_Intruct_Tool_Calling_V2 is a 1 billion parameter instruction-tuned Llama 3.2 model developed by nguyenthanhthuan_banhmi. It is specifically fine-tuned for function and tool calling, leveraging the nguyenthanhthuan/function-calling-sharegpt dataset. This model excels at interpreting natural language queries to generate structured tool calls, making it suitable for integrating with external systems and APIs, primarily in English.

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Model Overview

This model, nguyenthanhthuan/Llama_3.2_1B_Intruct_Tool_Calling_V2, is a specialized 1 billion parameter Llama 3.2-Instruct variant developed by nguyenthanhthuan_banhmi. It has been fine-tuned specifically for function and tool calling, utilizing the nguyenthanhthuan/function-calling-sharegpt dataset. The model is designed to parse natural language requests and output structured calls to predefined tools, supporting both basic arithmetic and complex API interactions.

Key Capabilities

  • Advanced Function/Tool Calling: Interprets user queries to generate structured tool calls for various functions like sending emails, getting weather info, searching the web, and setting reminders.
  • Langchain Integration: Seamlessly integrates with Langchain for easy development and deployment of tool-calling applications.
  • Ollama Compatibility: Designed for full compatibility with the Ollama platform, simplifying local deployment and usage.
  • Arithmetic Computation: Capable of performing basic arithmetic operations by invoking appropriate tools.

Good For

  • Automating Workflows: Ideal for developers building applications that require an LLM to interact with external APIs and services.
  • Intelligent Agents: Suitable for creating conversational agents that can perform actions based on user commands.
  • English-centric Tooling: Best utilized for use cases where function descriptions and user queries are primarily in English, as its advanced tool-calling capabilities are optimized for this language.

Finetunes
1 models