Triangle104/Qwen-3-14B-Gemini-v0.1-Q4_K_S-GGUF

This model was converted to GGUF format from Ba2han/Qwen-3-14B-Gemini-v0.1 using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

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Use "You are an assistant with reasoning capabilities." system message to trigger Gemini-style thinking.

Training Dataset

The fine-tuning dataset consists of ~300 diverse examples, 160 of which are directly from Gemini 2.5 Pro.

Model

Trained on unsloth version of Qwen3-14B (instruct). Keep in mind that it's slightly overfit since the training dataset was quite small.

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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/Qwen-3-14B-Gemini-v0.1-Q4_K_S-GGUF --hf-file qwen-3-14b-gemini-v0.1-q4_k_s.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/Qwen-3-14B-Gemini-v0.1-Q4_K_S-GGUF --hf-file qwen-3-14b-gemini-v0.1-q4_k_s.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/Qwen-3-14B-Gemini-v0.1-Q4_K_S-GGUF --hf-file qwen-3-14b-gemini-v0.1-q4_k_s.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/Qwen-3-14B-Gemini-v0.1-Q4_K_S-GGUF --hf-file qwen-3-14b-gemini-v0.1-q4_k_s.gguf -c 2048