Triangle104/14B-Qwen2.5-Kunou-v1-Q4_K_M-GGUF

This model was converted to GGUF format from Sao10K/14B-Qwen2.5-Kunou-v1 using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

---

Model details:

I do not really have anything planned for this model other than it being a generalist, and Roleplay Model? It was just something made and planned in minutes. This is the little sister variant, the small 14B version. Kunou's the name of an OC I worked on for a couple of years, for a... fanfic. mmm...

A kind-of successor to my smaller model series. It works pretty nicely I think? This version is basically a better, more cleaned up Dataset used on Euryale and Stheno.

Recommended Model Settings | Look, I just use these, they work fine enough. I don't even know how DRY or other meme samplers work. Your system prompt matters more anyway.

Prompt Format: ChatML Temperature: 1.1 min_p: 0.1

Special thanks to my wallet for funding this, my juniors who share a single braincell between them, and my current national service. There have been more stabbings, accidents out there this winter season. It's wild. Stay safe everyone.

Also sorry for the inactivity. Life was in the way. It still is, just less so, for now. Burnout is a thing, huh?

https://sao10k.carrd.co/ for contact.

---

Use with llama.cpp

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

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo Triangle104/14B-Qwen2.5-Kunou-v1-Q4_K_M-GGUF --hf-file 14b-qwen2.5-kunou-v1-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/14B-Qwen2.5-Kunou-v1-Q4_K_M-GGUF --hf-file 14b-qwen2.5-kunou-v1-q4_k_m.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps 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 Triangle104/14B-Qwen2.5-Kunou-v1-Q4_K_M-GGUF --hf-file 14b-qwen2.5-kunou-v1-q4_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/14B-Qwen2.5-Kunou-v1-Q4_K_M-GGUF --hf-file 14b-qwen2.5-kunou-v1-q4_k_m.gguf -c 2048