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ijohn07/GELab-Zero-4B-preview-Sico-Evolution-Q4_K_M-GGUF overview

ijohn07/GELab Zero 4B preview Sico Evolution Q4 K M GGUF This model was converted to GGUF format from microsoft/GELab Zero 4B preview Sico Evolution https://hu…

transformersggufgui-agentmobile-agentvision-languageqwen3-vllorallama-cppgguf-my-repoimage-text-to-textenzhbase_model:microsoft/GELab-Zero-4B-preview-Sico-Evolutionbase_model:adapter:microsoft/GELab-Zero-4B-preview-Sico-Evolutionlicense:apache-2.0endpoints_compatibleregion:us

Runs locally from ~2.33 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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gelab-zero-4b-preview-sico-evolution-q4_k_m.ggufGGUFQ4_K_M2.33 GBDownload

Model Details

Model IDijohn07/GELab-Zero-4B-preview-Sico-Evolution-Q4_K_M-GGUF
Authorijohn07
Pipelineimage-text-to-text
Licenseapache-2.0
Base modelmicrosoft/GELab-Zero-4B-preview-Sico-Evolution
Last modified2026-06-30T19:29:09.000Z

Model README

---

license: apache-2.0

base_model: microsoft/GELab-Zero-4B-preview-Sico-Evolution

library_name: transformers

pipeline_tag: image-text-to-text

language:

  • en
  • zh

tags:

  • gui-agent
  • mobile-agent
  • vision-language
  • qwen3-vl
  • lora
  • llama-cpp
  • gguf-my-repo

---

ijohn07/GELab-Zero-4B-preview-Sico-Evolution-Q4_K_M-GGUF

This model was converted to GGUF format from microsoft/GELab-Zero-4B-preview-Sico-Evolution 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 ijohn07/GELab-Zero-4B-preview-Sico-Evolution-Q4_K_M-GGUF --hf-file gelab-zero-4b-preview-sico-evolution-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo ijohn07/GELab-Zero-4B-preview-Sico-Evolution-Q4_K_M-GGUF --hf-file gelab-zero-4b-preview-sico-evolution-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 ijohn07/GELab-Zero-4B-preview-Sico-Evolution-Q4_K_M-GGUF --hf-file gelab-zero-4b-preview-sico-evolution-q4_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo ijohn07/GELab-Zero-4B-preview-Sico-Evolution-Q4_K_M-GGUF --hf-file gelab-zero-4b-preview-sico-evolution-q4_k_m.gguf -c 2048

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