PistachioAlt/Synatra-MCS-7B-v0.3-RP-Slerp

TEXT GENERATIONConcurrency Cost:1Model Size:7BQuant:FP8Ctx Length:4kPublished:Dec 11, 2023License:cc-by-nc-4.0Architecture:Transformer0.0K Open Weights Cold

PistachioAlt/Synatra-MCS-7B-v0.3-RP-Slerp is a 7 billion parameter language model created by PistachioAlt, built using a Slerp merge of Q-bert/MetaMath-Cybertron-Starling and maywell/Synatra-7B-v0.3-RP. This model leverages the strengths of its base models, combining mathematical reasoning capabilities with roleplay optimization. It is designed for tasks requiring both logical processing and nuanced conversational interaction within its 4096-token context window.

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Model Overview

PistachioAlt/Synatra-MCS-7B-v0.3-RP-Slerp is a 7 billion parameter language model developed by PistachioAlt. It is constructed through a Slerp merge of two distinct base models: Q-bert/MetaMath-Cybertron-Starling and maywell/Synatra-7B-v0.3-RP. This merging technique aims to combine their respective strengths.

Key Characteristics

  • Architecture: Based on a Slerp merge, which blends the weights of two source models.
  • Base Models: Integrates MetaMath-Cybertron-Starling (likely contributing to mathematical or reasoning capabilities) and Synatra-7B-v0.3-RP (indicating a focus on roleplay or conversational proficiency).
  • Parameter Count: 7 billion parameters, offering a balance between performance and computational efficiency.
  • Context Length: Supports a context window of 4096 tokens.

Intended Use Cases

This model is particularly well-suited for applications that require a combination of:

  • Reasoning Tasks: Benefiting from the MetaMath-Cybertron-Starling component.
  • Roleplay and Conversational AI: Leveraging the Synatra-7B-v0.3-RP component for nuanced interactions.
  • Hybrid Applications: Where both logical understanding and creative, character-driven responses are necessary.

Finetunes
3 models