---
library_name: transformers
tags:
- mistral
- quantized
- text-generation-inference
- roleplay
# - rp
# - uncensored
pipeline_tag: text-generation
inference: false
# language:
# - en
# FILL THE INFORMATION:
# Reference: ChaoticNeutrals/Eris_7B
# Author: ChaoticNeutrals
# Model: Eris_7B
# Llama.cpp version: b2308
---

## GGUF-Imatrix quantizations for [ChaoticNeutrals/Eris_7B](https://huggingface.co/ChaoticNeutrals/Eris_7B/).

All credits belong to the author.

## What does "Imatrix" mean?

It stands for **Importance Matrix**, a technique used to improve the quality of quantized models. <br>
[[1]](https://github.com/ggerganov/llama.cpp/discussions/5006/) <br>
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 and lead to better performance, especially when the calibration data is diverse. <br>
[[2]](https://github.com/ggerganov/llama.cpp/discussions/5263#discussioncomment-8395384/)

For --imatrix data, `imatrix-Eris_7B-F16.dat` was used.

Using [llama.cpp-bb2308](https://github.com/ggerganov/llama.cpp/releases/tag/bb2308/):

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

The new **IQ3_S** quant-option has shown to be better than the old Q3_K_S, so I added that instead of the later. Only supported in `koboldcpp-1.59.1` or higher.

If you want any specific quantization to be added, feel free to ask.

<!-- ## Model image: -->

## Original model information:

![image/png](https://cdn-uploads.huggingface.co/production/uploads/642265bc01c62c1e4102dc36/GZPRq5YCQO6v8v-aF7CQt.png)

# Jeitral: "Eris, the Greek goddess of chaos and discord."

Notes: Model should be excellent for both RP/Chat related tasks. Seems to be working in both Alpaca/Chatml.

```Collaborative effort from both @Jeiku and @Nitral involving what we currently felt were our best individual projects.```

We hope you enjoy! - The Chaotic Neutrals.

The following models were included in the merge:
* [ChaoticNeutrals/Prodigy_7B](https://huggingface.co/ChaoticNeutrals/Prodigy_7B)
* [Test157t/Prima-LelantaclesV6-7b](https://huggingface.co/Test157t/Prima-LelantaclesV6-7b)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
slices:
  - sources:
      - model: Test157t/Prima-LelantaclesV6-7b
        layer_range: [0, 32]
      - model: ChaoticNeutrals/Prodigy_7B
        layer_range: [0, 32]
merge_method: slerp
base_model: Test157t/Prima-LelantaclesV6-7b
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
```