Lewdiculous/Eris_PrimeV4-Vision-32k-7B-GGUF-IQ-Imatrix

#Roleplay #Multimodal #Vision

This repository hosts GGUF-IQ-Imatrix quants for Nitral-AI/Eris_PrimeV4-Vision-32k-7B.

"More stable and with better long context handling."

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.

Quants:

    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"
    ]

What does "Imatrix" mean?

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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 added roleplay chats was used, you can find it here. This was just to add a bit more diversity to the data.

Vision/multimodal capabilities:

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

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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 repository.

• You can load the mmproj 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:

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Steps performed:

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

Using the latest llama.cpp at the time.

Original model information:

Eris Prime: Version 4.0 32k

After many trials and tribulations we have a winner: A more coherent, format stable version of Eris Prime v4 with better long context handling.