MaziyarPanahi/airoboros-m-7b-3.1.2-dare-0.85-Mistral-7B-Instruct-v0.2-slerp

TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kPublished:Jan 12, 2024License:apache-2.0Architecture:Transformer Open Weights Cold

MaziyarPanahi/airoboros-m-7b-3.1.2-dare-0.85-Mistral-7B-Instruct-v0.2-slerp is a 7 billion parameter language model merged from Mistral-7B-Instruct-v0.2 and uukuguy/airoboros-m-7b-3.1.2-dare-0.85 using the slerp method. This model leverages the strengths of its base components, offering a 4096-token context length. It is designed for general instruction-following tasks, combining the robust base of Mistral with the fine-tuning characteristics of Airoboros.

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Overview

This model, airoboros-m-7b-3.1.2-dare-0.85-Mistral-7B-Instruct-v0.2-slerp, is a 7 billion parameter language model created by MaziyarPanahi. It is a merge of two distinct models: mistralai/Mistral-7B-Instruct-v0.2 and uukuguy/airoboros-m-7b-3.1.2-dare-0.85. The merge was performed using the slerp (spherical linear interpolation) method, which combines the weights of the base models to create a new, hybrid model.

Key Capabilities

  • Instruction Following: Inherits instruction-following capabilities from its base models, making it suitable for various prompt-based tasks.
  • General Purpose: Designed for a broad range of natural language understanding and generation applications.
  • Mistral-7B Foundation: Benefits from the strong base architecture and performance characteristics of the Mistral-7B-Instruct-v0.2 model.

Good For

  • Developers seeking a merged model that combines the strengths of a robust instruction-tuned base with additional fine-tuning.
  • Applications requiring a 7B parameter model with a 4096-token context window for general text generation and conversational AI.
  • Experimentation with merged models to explore different performance profiles.