Noromaid-v0.4-Mixtral-Instruct-8x7b-Zloss-GGUF

Maintainer: NeverSleep

Total Score

40

Last updated 9/6/2024

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PropertyValue
Run this modelRun on HuggingFace
API specView on HuggingFace
Github linkNo Github link provided
Paper linkNo paper link provided

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Model overview

The Noromaid-v0.4-Mixtral-Instruct-8x7b-Zloss-GGUF model is an experimental large language model (LLM) created by NeverSleep. It builds upon the previous Noromaid-v0.1-Mixtral-Instruct-8x7b-v3 model, incorporating the Zloss fork of the Charles dataset to address issues the previous model had. The model uses the Chatml prompting format, but not the special token, as the author found that directly merging the finetuned model with the base model at full weight was too much.

Model inputs and outputs

Inputs

  • Users provide prompts in the Chatml format, without the special token

Outputs

  • The model generates text responses based on the provided prompts

Capabilities

The Noromaid-v0.4-Mixtral-Instruct-8x7b-Zloss-GGUF model is suitable for roleplaying (RP) and erotic roleplaying (ERP) tasks. It has been improved to address issues with the previous Noromaid-v0.1 model, and the author suggests it should provide better performance.

What can I use it for?

The Noromaid-v0.4-Mixtral-Instruct-8x7b-Zloss-GGUF model can be used for various RP and ERP applications, such as interactive storytelling, character development, and collaborative worldbuilding. While the model is experimental, it may be a useful tool for users interested in these types of creative writing and roleplay activities.

Things to try

Users may want to experiment with different prompting styles and techniques to see how the model responds. Additionally, trying the model with various RP and ERP scenarios could help uncover its strengths and limitations. As an experimental model, it's important to approach using it with appropriate caution and keep in mind that not everything may work as expected.



This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!

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