dphn/fc-dolphin-2.6-mistral-7b-dpo-laser

TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kPublished:Feb 9, 2024License:apache-2.0Architecture:Transformer0.0K Open Weights Cold

The dphn/fc-dolphin-2.6-mistral-7b-dpo-laser is a 7 billion parameter Mistral-based language model developed by David, Fernando, and Eric, sponsored by VAGO Solutions and HyperSpace.Ai. It is specifically fine-tuned for function calling, utilizing a novel training technique that partially freezes the model to prevent catastrophic forgetting. This model excels at integrating external tools and APIs into its responses, making it suitable for applications requiring structured interactions.

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Model Overview

The dphn/fc-dolphin-2.6-mistral-7b-dpo-laser is a 7 billion parameter model built upon the Mistral architecture, developed by David, Fernando, and Eric. It is a specialized version of cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser, with a primary focus on enhancing function calling capabilities.

Key Capabilities

  • Function Calling: The model is specifically trained on a variation of the glaive function calling v2 dataset, enabling it to understand and invoke external functions. It uses a distinct <functioncall> token and JSON format for function invocation.
  • Catastrophic Forgetting Prevention: It incorporates a novel training technique, inspired by laserRMT, which involves partially freezing the model. This method is designed to prevent the loss of previously acquired knowledge, a critical advantage when teaching specific skills like function calling.
  • ChatML Syntax: The model is designed to be used with ChatML syntax for representing conversational turns, aligning with other Dolphin models.

Good For

  • Tool Integration: Ideal for applications that require the language model to interact with external tools, APIs, or databases by generating structured function calls.
  • Automated Workflows: Suitable for building intelligent agents that can perform actions based on user prompts by invoking predefined functions.
  • Developers requiring robust function calling: Offers a specialized solution for integrating LLMs into systems where precise and reliable function invocation is crucial.

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