actionpace/Chronorctypus-Limarobormes-13b
TEXT GENERATIONConcurrency Cost:1Model Size:13BQuant:FP8Ctx Length:4kPublished:Aug 30, 2023License:otherArchitecture:Transformer0.0K Cold

The actionpace/Chronorctypus-Limarobormes-13b is a 13 billion parameter language model, derived from a merge of several Llama2-based models including OpenOrca-Platypus2-13B, limarp-13b-merged, Nous-Hermes-Llama2-13b, chronos-13b, and airoboros-l2-13b-gpt4-1.4.1. This model is designed to combine the strengths of its constituent models, offering a versatile foundation for various natural language processing tasks. It provides a context length of 4096 tokens, making it suitable for applications requiring moderate input and output lengths.

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Overview

The actionpace/Chronorctypus-Limarobormes-13b is a 13 billion parameter language model created by actionpace through a merge of several established Llama2-based models. This merge aims to consolidate the diverse capabilities of its source models into a single, more robust offering. The model supports a context length of 4096 tokens, providing a balanced capacity for processing and generating text.

Key Characteristics

This model is a composite of the following foundational models:

  • Open-Orca/OpenOrca-Platypus2-13B: Known for its instruction-following and reasoning abilities.
  • Oniichat/limarp-13b-merged: Contributes to general language understanding and generation.
  • NousResearch/Nous-Hermes-Llama2-13b: Often recognized for its strong performance across various benchmarks.
  • elinas/chronos-13b: Adds to the model's overall linguistic competence.
  • jondurbin/airoboros-l2-13b-gpt4-1.4.1: Enhances the model's instruction-tuning and conversational capabilities.

Potential Use Cases

Given its merged architecture, Chronorctypus-Limarobormes-13b is suitable for a range of applications where a general-purpose, instruction-tuned language model is beneficial. Its 13B parameter count offers a good balance between performance and computational requirements. The model's diverse lineage suggests potential strengths in:

  • General text generation: Creating coherent and contextually relevant text.
  • Instruction following: Responding accurately to user prompts and commands.
  • Conversational AI: Engaging in multi-turn dialogues.
  • Reasoning tasks: Handling tasks that require logical inference, benefiting from the contributions of models like OpenOrca-Platypus2.

This model is a good candidate for developers looking for a versatile 13B model that integrates the strengths of several well-regarded Llama2 derivatives.