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---
license: other
tags:
- gguf
- quantized
- roleplay
- multimodal
- vision
- sillytavern
- merge
- mistral
---
This repository hosts GGUF-IQ-Imatrix quants for [ChaoticNeutrals/Eris_PrimeV3-Vision-7B](https://huggingface.co/ChaoticNeutrals/Eris_PrimeV3-Vision-7B).
This is a #multimodal model that also has vision capabilities. Read the full card information if that is your use case.
Quants:
```python
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?**
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]](https://github.com/ggerganov/llama.cpp/discussions/5006) [[2]](https://github.com/ggerganov/llama.cpp/discussions/5263#discussioncomment-8395384)
For imatrix data generation, kalomaze's `groups_merged.txt` with added roleplay chats was used, you can find it [here](https://huggingface.co/Lewdiculous/Datura_7B-GGUF-Imatrix/blob/main/imatrix-with-rp-format-data.txt). This was just to add a bit more diversity to the data.
# Vision/multimodal capabilities:
<details><summary>
Click here to see how this would work in practice in a roleplay chat.
</summary>
</details><br>
<details><summary>
Click here to see what your SillyTavern Image Captions extension settings should look like.
</summary>
</details><br>
**If you want to use vision functionality:**
* Make sure you are using the latest version of [KoboldCpp](https://github.com/LostRuins/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](https://huggingface.co/cjpais/llava-1.6-mistral-7b-gguf/blob/main/mmproj-model-f16.gguf).
* 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:
**Steps performed:**
```
Base⇢ GGUF(F16)⇢ Imatrix-Data(F16)⇢ GGUF(Imatrix-Quants)
```
*Using the latest llama.cpp at the time.*
# Original model information:
Eris with vision capabilites supported by KCPP (required for vision support): https://huggingface.co/koboldcpp/mmproj/blob/main/mistral-7b-mmproj-v1.5-Q4_1.gguf
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* [InferenceIllusionist/Excalibur-7b](https://huggingface.co/InferenceIllusionist/Excalibur-7b)
* [ChaoticNeutrals/Eris_Prime-V2-7B](https://huggingface.co/ChaoticNeutrals/Eris_Prime-V2-7B)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
slices:
- sources:
- model: ChaoticNeutrals/Eris_Prime-V2-7B
layer_range: [0, 32]
- model: InferenceIllusionist/Excalibur-7b
layer_range: [0, 32]
merge_method: slerp
base_model: ChaoticNeutrals/Eris_Prime-V2-7B
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
dtype: bfloat16
``` |