Lewdiculous/Nyanade_Stunna-Maid-7B-GGUF-IQ-Imatrix

#Roleplay #Multimodal #Vision

This repository hosts GGUF-IQ-Imatrix quants for Nitral-AI/Nyanade_Stunna-Maid-7B.

Recommended starting SillyTavern presets here.

This is a #multimodal model that also has #vision capabilities.
Read the full card information if you also want to use that functionality.

"Expected to be used with up to --contextsize 8192."

What does "Imatrix" mean?

⇲ Click here to expand/hide more information about this topic.

It stands for Importance Matrix, a technique used to improve the quality of quantized models. The Imatrix is calculated based on calibration data, and it helps determine the importance of different model activations during the quantization process. The idea is to preserve the most important information during quantization, which can help reduce the loss of model performance, especially when the calibration data is diverse. [1] [2]

For imatrix data generation, kalomaze's groups_merged.txt with additional roleplay chats was used, you can find it here. This was just to add a bit more diversity to the data with the intended use case in mind.

Vision/multimodal capabilities:

⇲ Click here to expand/hide how this would work in practice in a roleplay chat.

⇲ Click here to expand/hide what your SillyTavern Image Captions extension settings should look like.

If you want to use vision functionality:

• Make sure you are using the latest version of KoboldCpp.

To use the multimodal capabilities of this model, such as vision, you also need to load the specified mmproj file, you can get it here or as uploaded in the mmproj folder in the repository.

• You can load the mmproj file by using the corresponding section in the interface:

• For CLI users, you can load the mmproj file by adding the respective flag to your usual command:

--mmproj your-mmproj-file.gguf

Quantization information:

⇲ Click here to expand/hide more information about this topic.

    quantization_options = [
        "Q4_K_M", "Q4_K_S", "IQ4_XS", "Q5_K_M", "Q5_K_S",
        "Q6_K", "Q8_0", "IQ3_M", "IQ3_S", "IQ3_XXS"
    ]

Steps performed:

Base⇢ GGUF(F16)⇢ Imatrix-Data(F16)⇢ GGUF(Imatrix-Quants)

Using the latest llama.cpp at the time.