---
base_model:
- macadeliccc/WestLake-7B-v2-laser-truthy-dpo
- ChaoticNeutrals/This_is_fine_7B
library_name: transformers
tags:
- mistral
- quantized
- text-generation-inference
- mergekit
- merge
pipeline_tag: text-generation
inference: false
---
# [Uploading Q3, Q4, Q5, Q6 and Q8.]

# **GGUF-Imatrix quantizations for [ChaoticNeutrals/Prodigy_7B](https://huggingface.co/ChaoticNeutrals/Prodigy_7B/).**

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

All credits belong to the [creator](https://huggingface.co/ChaoticNeutrals/).

`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.

Using [llama.cpp](https://github.com/ggerganov/llama.cpp/)-[b2277](https://github.com/ggerganov/llama.cpp/releases/tag/b2277).

For --imatrix data, `imatrix-Prodigy_7B-F16.dat` was used.

# Original model information:

# Wing

![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/626dfb8786671a29c715f8a9/S-E_CADzfAg3xaVX01rdx.jpeg)

This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

## Merge Details
### Merge Method

This model was merged using the SLERP merge method.

### Models Merged

The following models were included in the merge:
* [macadeliccc/WestLake-7B-v2-laser-truthy-dpo](https://huggingface.co/macadeliccc/WestLake-7B-v2-laser-truthy-dpo)
* [ChaoticNeutrals/This_is_fine_7B](https://huggingface.co/ChaoticNeutrals/This_is_fine_7B)

### Configuration

The following YAML configuration was used to produce this model:

```yaml
slices:
  - sources:
      - model: ChaoticNeutrals/This_is_fine_7B
        layer_range: [0, 32]
      - model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo
        layer_range: [0, 32]
merge_method: slerp
base_model: macadeliccc/WestLake-7B-v2-laser-truthy-dpo
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: float16
```