Triangle104/DeepSeek-R1-0528-Qwen3-8B-Esper3-Q6_K-GGUF

This model was converted to GGUF format from ValiantLabs/DeepSeek-R1-0528-Qwen3-8B-Esper3 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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Esper 3 is a coding, architecture, and DevOps reasoning specialist built on Qwen 3.

• Finetuned on our DevOps and architecture reasoning and code reasoning data generated with Deepseek R1!
• Improved general and creative reasoning to supplement problem-solving and general chat performance.
• Small model sizes allow running on local desktop and mobile, plus super-fast server inference!

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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/DeepSeek-R1-0528-Qwen3-8B-Esper3-Q6_K-GGUF --hf-file deepseek-r1-0528-qwen3-8b-esper3-q6_k.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/DeepSeek-R1-0528-Qwen3-8B-Esper3-Q6_K-GGUF --hf-file deepseek-r1-0528-qwen3-8b-esper3-q6_k.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/DeepSeek-R1-0528-Qwen3-8B-Esper3-Q6_K-GGUF --hf-file deepseek-r1-0528-qwen3-8b-esper3-q6_k.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/DeepSeek-R1-0528-Qwen3-8B-Esper3-Q6_K-GGUF --hf-file deepseek-r1-0528-qwen3-8b-esper3-q6_k.gguf -c 2048