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TULLUS/Qwen1.5-MoE-A2.7B-Q4_K_M-GGUF overview

TULLUS/Qwen1.5 MoE A2.7B Q4 K M GGUF This model was converted to GGUF format from TULLUS/Qwen1.5 MoE A2.7B https://huggingface.co/TULLUS/Qwen1.5 MoE A2.7B usin…

ggufpretrainedmoellama-cppgguf-my-repotext-generationenbase_model:TULLUS/Qwen1.5-MoE-A2.7Bbase_model:quantized:TULLUS/Qwen1.5-MoE-A2.7Blicense:otherendpoints_compatibleregion:usconversational

Runs locally from ~8.84 GB disk (12 GB VRAM class GPUs with llama.cpp / guIDE).

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text-generation
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Repository Files & Downloads

1 GGUF files detected
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qwen1.5-moe-a2.7b-q4_k_m.ggufGGUFQ4_K_M8.84 GBDownload

Model Details

Model IDTULLUS/Qwen1.5-MoE-A2.7B-Q4_K_M-GGUF
AuthorTULLUS
Pipelinetext-generation
Licenseother
Base modelTULLUS/Qwen1.5-MoE-A2.7B
Last modified2026-09-09T09:26:51.000Z

Model README

---

license: other

license_name: tongyi-qianwen

license_link: https://huggingface.co/Qwen/Qwen1.5-MoE-A2.7B/blob/main/LICENSE

language:

  • en

pipeline_tag: text-generation

tags:

  • pretrained
  • moe
  • llama-cpp
  • gguf-my-repo

base_model: TULLUS/Qwen1.5-MoE-A2.7B

---

TULLUS/Qwen1.5-MoE-A2.7B-Q4_K_M-GGUF

This model was converted to GGUF format from TULLUS/Qwen1.5-MoE-A2.7B using llama.cpp via the ggml.ai's GGUF-my-repo space.

Refer to the original model card for more details on the model.

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 TULLUS/Qwen1.5-MoE-A2.7B-Q4_K_M-GGUF --hf-file qwen1.5-moe-a2.7b-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo TULLUS/Qwen1.5-MoE-A2.7B-Q4_K_M-GGUF --hf-file qwen1.5-moe-a2.7b-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 TULLUS/Qwen1.5-MoE-A2.7B-Q4_K_M-GGUF --hf-file qwen1.5-moe-a2.7b-q4_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo TULLUS/Qwen1.5-MoE-A2.7B-Q4_K_M-GGUF --hf-file qwen1.5-moe-a2.7b-q4_k_m.gguf -c 2048

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