Triangle104/Capricornus-MoT-1.7B-Supreme1-Q5_K_M-GGUF

This model was converted to GGUF format from prithivMLmods/Capricornus-MoT-1.7B-Supreme1 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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Capricornus-MoT-1.7B-Supreme1 is a high-precision, multi-domain expert model fine-tuned from Qwen3-1.7B, built for code generation, mathematical reasoning, scientific analysis, and open technical inference. Trained on the Mixture of Thoughts (MoT) dataset with combined expert clusters in code, math, and science, and enhanced with an Open Code Reasoning dataset, it delivers powerful symbolic and structured outputs in a wide range of STEM and reasoning domains.

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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/Capricornus-MoT-1.7B-Supreme1-Q5_K_M-GGUF --hf-file capricornus-mot-1.7b-supreme1-q5_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/Capricornus-MoT-1.7B-Supreme1-Q5_K_M-GGUF --hf-file capricornus-mot-1.7b-supreme1-q5_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/Capricornus-MoT-1.7B-Supreme1-Q5_K_M-GGUF --hf-file capricornus-mot-1.7b-supreme1-q5_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/Capricornus-MoT-1.7B-Supreme1-Q5_K_M-GGUF --hf-file capricornus-mot-1.7b-supreme1-q5_k_m.gguf -c 2048