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

# Triangle104/Rombos-Qwen2.5-Writer-32b-Q5_K_S-GGUF
This model was converted to GGUF format from [`SubtleOne/Rombos-Qwen2.5-Writer-32b`](https://huggingface.co./SubtleOne/Rombos-Qwen2.5-Writer-32b) 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/Rombos-Qwen2.5-Writer-32b) for more details on the model.

---
Model details:
-
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 I 
enjoyed it in my DnD RPG campaign.



	
		
	

		Merge
	



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



	
		
	

		Merge Method
	



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



	
		
	

		Models Merged
	



The following models were included in the merge:


EVA-UNIT-01/EVA-Qwen2.5-32B-v0.2
allura-org/Qwen2.5-32b-RP-Ink
nbeerbower/Qwen2.5-Gutenberg-Doppel-32B



	
		
	

		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
dtype: bfloat16
tokenizer_source: union
merge_method: dare_ties
models:
  - model: EVA-UNIT-01/EVA-Qwen2.5-32B-v0.2
    parameters:
      weight: [0.4]
      density: [0.55]
  - model: nbeerbower/Qwen2.5-Gutenberg-Doppel-32B
    parameters:
      weight: [0.3]
      density: [0.55]
  - model: allura-org/Qwen2.5-32b-RP-Ink
    parameters:
      weight: [0.4]
      density: [0.55]

---
## 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/Rombos-Qwen2.5-Writer-32b-Q5_K_S-GGUF --hf-file rombos-qwen2.5-writer-32b-q5_k_s.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/Rombos-Qwen2.5-Writer-32b-Q5_K_S-GGUF --hf-file rombos-qwen2.5-writer-32b-q5_k_s.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/Rombos-Qwen2.5-Writer-32b-Q5_K_S-GGUF --hf-file rombos-qwen2.5-writer-32b-q5_k_s.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/Rombos-Qwen2.5-Writer-32b-Q5_K_S-GGUF --hf-file rombos-qwen2.5-writer-32b-q5_k_s.gguf -c 2048
```