AtAndDev/Ogno-Monarch-Neurotic-7B-Dare-Ties

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

Ogno-Monarch-Neurotic-7B-Dare-Ties is a 7 billion parameter language model created by AtAndDev through a DARE TIES merge of bardsai/jaskier-7b-dpo-v5.6 and eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO. This model leverages the strengths of its constituent models, focusing on instruction-following and preference alignment. It is suitable for tasks requiring nuanced responses and adherence to specific directives within its 4096-token context window.

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Model Overview

Ogno-Monarch-Neurotic-7B-Dare-Ties is a 7 billion parameter language model developed by AtAndDev. It was created using the DARE TIES merging method, combining two distinct base models: bardsai/jaskier-7b-dpo-v5.6 and eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO. This merging strategy aims to synthesize the capabilities of its components, particularly those related to instruction following and preference alignment.

Key Characteristics

  • Architecture: A merged model, combining two DPO (Direct Preference Optimization) fine-tuned models.
  • Parameter Count: 7 billion parameters, offering a balance between performance and computational efficiency.
  • Context Length: Supports a context window of 4096 tokens, allowing for processing moderately long inputs.
  • Merging Method: Utilizes the dare_ties method from mergekit, with specific density and weight parameters applied to each base model.

Use Cases

This model is particularly well-suited for applications that benefit from:

  • Instruction Following: Generating responses that adhere closely to given instructions.
  • Preference Alignment: Producing outputs that are aligned with human preferences, inherited from its DPO-trained base models.
  • General Text Generation: Capable of various language generation tasks where a 7B model is appropriate.