---
base_model: SubtleOne/Qwen2.5-32b-Erudite-Writer
library_name: transformers
tags:
- mergekit
- merge
- llama-cpp
- gguf-my-repo
license: apache-2.0
---

# Triangle104/Qwen2.5-32b-Erudite-Writer-Q6_K-GGUF
This model was converted to GGUF format from [`SubtleOne/Qwen2.5-32b-Erudite-Writer`](https://huggingface.co/SubtleOne/Qwen2.5-32b-Erudite-Writer) 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/SubtleOne/Qwen2.5-32b-Erudite-Writer) for more details on the model.

---
This model is a merge using Rombos's top-ranked 32b model, based on Qwen 2.5, and merging three creative writing finetunes. The creative content is a serious upgrade over the base it started with and has a much more literary style than the previous Writer model. I won't call it better or worse, merely a very distinct flavor and style. I quite like it, and enjoin you to try it as well. Enjoy!

Merge Method

This model was merged using the DELLA merge method using rombodawg/Rombos-LLM-V2.5-Qwen-32b as a base.

Models Merged

The following models were included in the merge:

    nbeerbower/Qwen2.5-Gutenberg-Doppel-32B
    ArliAI/Qwen2.5-32B-ArliAI-RPMax-v1.3
    EVA-UNIT-01/EVA-Qwen2.5-32B-v0.2

Configuration

The following YAML configuration was used to produce this model:

base_model: rombodawg/Rombos-LLM-V2.5-Qwen-32b
parameters:
  int8_mask: true
  rescale: false
  normalize: true
  lambda: 1.04
  epsilon: 0.05
dtype: bfloat16
tokenizer_source: union
merge_method: della
models:
  - model: EVA-UNIT-01/EVA-Qwen2.5-32B-v0.2
    parameters:
      weight: [0.40]
      density: [0.53]
  - model: nbeerbower/Qwen2.5-Gutenberg-Doppel-32B
    parameters:
      weight: [0.30]
      density: [0.53]   
  - model: ArliAI/Qwen2.5-32B-ArliAI-RPMax-v1.3
    parameters:
      weight: [0.40]
      density: [0.53]  

---
## 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 Triangle104/Qwen2.5-32b-Erudite-Writer-Q6_K-GGUF --hf-file qwen2.5-32b-erudite-writer-q6_k.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/Qwen2.5-32b-Erudite-Writer-Q6_K-GGUF --hf-file qwen2.5-32b-erudite-writer-q6_k.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 Triangle104/Qwen2.5-32b-Erudite-Writer-Q6_K-GGUF --hf-file qwen2.5-32b-erudite-writer-q6_k.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/Qwen2.5-32b-Erudite-Writer-Q6_K-GGUF --hf-file qwen2.5-32b-erudite-writer-q6_k.gguf -c 2048
```