merge

This is a merge of pre-trained language models created using mergekit.
Merge Details
Merge Method

This model was merged using the SLERP merge method.
Models Merged

The following models were included in the merge:

    rombodawg/Rombos-LLM-V2.5-Qwen-32b
    fblgit/TheBeagle-v2beta-32B-MGS

Configuration

The following YAML configuration was used to produce this model:

slices:
- sources:
  - model: fblgit/TheBeagle-v2beta-32B-MGS
    layer_range:
    - 0
    - 64
  - model: rombodawg/Rombos-LLM-V2.5-Qwen-32b
    layer_range:
    - 0
    - 64
merge_method: slerp
base_model: rombodawg/Rombos-LLM-V2.5-Qwen-32b
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

---
base_model: mergekit-community/mergekit-slerp-uavuhik
library_name: transformers
tags:
- mergekit
- merge
- llama-cpp
- gguf-my-repo
---

# Insanelycool/mergekit-slerp-uavuhik-Q8_0-GGUF
This model was converted to GGUF format from [`mergekit-community/mergekit-slerp-uavuhik`](https://huggingface.co/mergekit-community/mergekit-slerp-uavuhik) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/mergekit-community/mergekit-slerp-uavuhik) for more details on the model.

## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo Insanelycool/mergekit-slerp-uavuhik-Q8_0-GGUF --hf-file mergekit-slerp-uavuhik-q8_0.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Insanelycool/mergekit-slerp-uavuhik-Q8_0-GGUF --hf-file mergekit-slerp-uavuhik-q8_0.gguf -c 2048
```

Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```

Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```

Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo Insanelycool/mergekit-slerp-uavuhik-Q8_0-GGUF --hf-file mergekit-slerp-uavuhik-q8_0.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Insanelycool/mergekit-slerp-uavuhik-Q8_0-GGUF --hf-file mergekit-slerp-uavuhik-q8_0.gguf -c 2048
```