Llama-3-Lumimaid-8B-v0.1-OAS-GGUF-IQ-Imatrix
Maintainer: Lewdiculous
51
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| Property | Value |
|---|---|
| Run this model | Run on HuggingFace |
| API spec | View on HuggingFace |
| Github link | No Github link provided |
| Paper link | No paper link provided |
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Model overview
The Llama-3-Lumimaid-8B-v0.1-OAS-GGUF-IQ-Imatrix model is a version of the Llama-3 language model that has been fine-tuned by the maintainer Lewdiculous. This model uses the Llama3 prompting format and has been trained on a balance of role-playing (RP) and non-RP datasets, with the goal of creating a model that is capable but not overly "horny". The model has also received the Orthogonal Activation Steering (OAS) treatment, which means it will rarely refuse any request.
Model inputs and outputs
The Llama-3-Lumimaid-8B-v0.1-OAS-GGUF-IQ-Imatrix model is a text-to-text model, meaning it takes text as input and generates text as output. The model can be used for a variety of natural language processing tasks, such as language generation, summarization, and translation.
Inputs
- Text prompts
Outputs
- Generated text based on the input prompts
Capabilities
The Llama-3-Lumimaid-8B-v0.1-OAS-GGUF-IQ-Imatrix model is capable of generating coherent and relevant text in response to a wide range of prompts, thanks to its training on a balance of RP and non-RP datasets. The OAS treatment also means the model is unlikely to refuse requests, making it a flexible and powerful tool for language generation tasks.
What can I use it for?
The Llama-3-Lumimaid-8B-v0.1-OAS-GGUF-IQ-Imatrix model can be used for a variety of applications, such as creative writing, dialogue generation, and content creation. The maintainer, Lewdiculous, has also provided some compatible SillyTavern presets and Virt's Roleplay Presets that can be used to integrate the model into various chatbot and virtual assistant applications.
Things to try
One interesting aspect of the Llama-3-Lumimaid-8B-v0.1-OAS-GGUF-IQ-Imatrix model is its ability to generate text that balances RP and non-RP content. Users can experiment with different prompts to see how the model responds, and explore the nuances of its language generation capabilities. Additionally, the OAS treatment means the model is unlikely to refuse requests, allowing users to push the boundaries of what the model can do.
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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