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FINAL-Bench
/
POCKET-26B-GGUF

Text Generation
GGUF
llama.cpp
conversational
on-device
mobile
korean
korean-llm
cpu
local-llm
edge
gemma
gemma4
mixture-of-experts
Mixture of Experts
pocket
vidraft
imatrix
Model card Files Files and versions
xet
Community
1

Instructions to use FINAL-Bench/POCKET-26B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • llama.cpp

    How to use FINAL-Bench/POCKET-26B-GGUF with llama.cpp:

    Install (macOS, Linux)
    curl -LsSf https://llama.app/install.sh | sh
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf FINAL-Bench/POCKET-26B-GGUF:Q2_K
    # Run inference directly in the terminal:
    llama cli -hf FINAL-Bench/POCKET-26B-GGUF:Q2_K
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf FINAL-Bench/POCKET-26B-GGUF:Q2_K
    # Run inference directly in the terminal:
    llama cli -hf FINAL-Bench/POCKET-26B-GGUF:Q2_K
    Use pre-built binary
    # Download pre-built binary from:
    # https://github.com/ggerganov/llama.cpp/releases
    # Start a local OpenAI-compatible server with a web UI:
    ./llama-server -hf FINAL-Bench/POCKET-26B-GGUF:Q2_K
    # Run inference directly in the terminal:
    ./llama-cli -hf FINAL-Bench/POCKET-26B-GGUF:Q2_K
    Build from source code
    git clone https://github.com/ggerganov/llama.cpp.git
    cd llama.cpp
    cmake -B build
    cmake --build build -j --target llama-server llama-cli
    # Start a local OpenAI-compatible server with a web UI:
    ./build/bin/llama-server -hf FINAL-Bench/POCKET-26B-GGUF:Q2_K
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf FINAL-Bench/POCKET-26B-GGUF:Q2_K
    Use Docker
    docker model run hf.co/FINAL-Bench/POCKET-26B-GGUF:Q2_K
  • LM Studio
  • Jan
  • vLLM

    How to use FINAL-Bench/POCKET-26B-GGUF with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "FINAL-Bench/POCKET-26B-GGUF"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "FINAL-Bench/POCKET-26B-GGUF",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/FINAL-Bench/POCKET-26B-GGUF:Q2_K
  • Ollama

    How to use FINAL-Bench/POCKET-26B-GGUF with Ollama:

    ollama run hf.co/FINAL-Bench/POCKET-26B-GGUF:Q2_K
  • Unsloth Desktop
  • Docker Model Runner

    How to use FINAL-Bench/POCKET-26B-GGUF with Docker Model Runner:

    docker model run hf.co/FINAL-Bench/POCKET-26B-GGUF:Q2_K
  • Lemonade

    How to use FINAL-Bench/POCKET-26B-GGUF with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull FINAL-Bench/POCKET-26B-GGUF:Q2_K
    Run and chat with the model
    lemonade run user.POCKET-26B-GGUF-Q2_K
    List all available models
    lemonade list
  • Atomic Chat
POCKET-26B-GGUF
27.9 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 15 commits
SeaWolf-AI's picture
SeaWolf-AI
POCKET family: add POCKET-Qwen3.8-Flash-Next (180B on a laptop), cross-link all 8 POCKET repos
1f9ee55 verified 13 days ago
  • .gitattributes
    1.76 kB
    rename files POCKET-Gemma-KR-* -> POCKET-26B-* 3 months ago
  • POCKET-26B-Q2_K.gguf
    11.1 GB
    xet
    rename files POCKET-Gemma-KR-* -> POCKET-26B-* 3 months ago
  • POCKET-26B-Q4_K_M.gguf
    16.8 GB
    xet
    rename files POCKET-Gemma-KR-* -> POCKET-26B-* 3 months ago
  • README.md
    8.43 kB
    POCKET family: add POCKET-Qwen3.8-Flash-Next (180B on a laptop), cross-link all 8 POCKET repos 13 days ago
  • pocket26_hero.svg
    3 kB
    add POCKET-26B hero image 3 months ago