inference: false
tags:
- gguf
- quantized
- roleplay
- multimodal
- vision
- llava
- sillytavern
- merge
- mistral
- conversational
base_model:
- Nitral-AI/Eris_PrimeV4.20-Vision-32k-7B
- Nitral-AI/KukulStanta-7B
#Roleplay #Multimodal #Vision
This repository hosts GGUF-IQ-Imatrix quants for Nitral-AI/Kukul-Stanta-0.420-32k-7B-0.2.
"It's Kukul time!"
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.
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 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.
⇲ 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 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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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.