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MaziyarPanahi
/
openthaigpt1.5-14b-instruct-GGUF

Text Generation
GGUF
mistral
quantized
2-bit
3-bit
4-bit precision
5-bit
6-bit
8-bit precision
GGUF
conversational
Model card Files Files and versions
xet
Community
1

Instructions to use MaziyarPanahi/openthaigpt1.5-14b-instruct-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 MaziyarPanahi/openthaigpt1.5-14b-instruct-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 MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M
    # Run inference directly in the terminal:
    llama cli -hf MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M
    # Run inference directly in the terminal:
    llama cli -hf MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M
    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 MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M
    # Run inference directly in the terminal:
    ./llama-cli -hf MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M
    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 MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M
    Use Docker
    docker model run hf.co/MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M
  • LM Studio
  • Jan
  • vLLM

    How to use MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "MaziyarPanahi/openthaigpt1.5-14b-instruct-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": "MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M
  • Ollama

    How to use MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF with Ollama:

    ollama run hf.co/MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M
  • Unsloth Desktop
  • Pi

    How to use MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF with Pi:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M
    Configure the model in Pi
    # Install Pi:
    npm install -g @earendil-works/pi-coding-agent
    # Add to ~/.pi/agent/models.json:
    {
      "providers": {
        "llama-cpp": {
          "baseUrl": "http://localhost:8080/v1",
          "api": "openai-completions",
          "apiKey": "none",
          "models": [
            {
              "id": "MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Docker Model Runner

    How to use MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF with Docker Model Runner:

    docker model run hf.co/MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M
  • Lemonade

    How to use MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M
    Run and chat with the model
    lemonade run user.openthaigpt1.5-14b-instruct-GGUF-Q5_K_M
    List all available models
    lemonade list
  • Hermes Agent

    How to use MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF with Hermes Agent:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M
    Configure Hermes
    # Install Hermes:
    curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
    hermes setup
    # Point Hermes at the local server:
    hermes config set model.provider custom
    hermes config set model.base_url http://127.0.0.1:8080/v1
    hermes config set model.default MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M
    Run Hermes
    hermes
  • Atomic Chat
  • OpenClaw

    How to use MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF with OpenClaw:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M
    Configure OpenClaw
    # Install OpenClaw:
    npm install -g openclaw@latest
    # Register the local server and set it as the default model:
    openclaw onboard --non-interactive --mode local \
      --auth-choice custom-api-key \
      --custom-base-url http://127.0.0.1:8080/v1 \
      --custom-model-id "MaziyarPanahi/openthaigpt1.5-14b-instruct-GGUF:Q5_K_M" \
      --custom-provider-id llama-cpp \
      --custom-compatibility openai \
      --custom-text-input \
      --accept-risk \
      --skip-health
    Run OpenClaw
    openclaw agent --local --agent main --message "Hello from Hugging Face"
openthaigpt1.5-14b-instruct-GGUF
78.2 GB
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  • 1 contributor
History: 7 commits
MaziyarPanahi's picture
MaziyarPanahi
0c847f712d6de7170f3a004259d9fd93f2ff366d5209298913e601419012de0c
2e96312 verified almost 2 years ago
  • .gitattributes
    1.97 kB
    0c847f712d6de7170f3a004259d9fd93f2ff366d5209298913e601419012de0c almost 2 years ago
  • README.md
    3.06 kB
    0c847f712d6de7170f3a004259d9fd93f2ff366d5209298913e601419012de0c almost 2 years ago
  • openthaigpt1.5-14b-instruct-GGUF_imatrix.dat
    8.56 MB
    xet
    0c847f712d6de7170f3a004259d9fd93f2ff366d5209298913e601419012de0c almost 2 years ago
  • openthaigpt1.5-14b-instruct.Q5_K_M.gguf
    10.5 GB
    xet
    5017566282f67512d2a92261161446262e822301c2d20dc528dc69e6024888e1 almost 2 years ago
  • openthaigpt1.5-14b-instruct.Q5_K_S.gguf
    10.3 GB
    xet
    2637e3fd382ae59966c45a83cfdb994cdb083c703aeaed7ebcfe3c1af090c432 almost 2 years ago
  • openthaigpt1.5-14b-instruct.Q6_K.gguf
    12.1 GB
    xet
    b74827aded3776ac9594c279f7619009a056969febb0684b27bfe1300a4a89c4 almost 2 years ago
  • openthaigpt1.5-14b-instruct.Q8_0.gguf
    15.7 GB
    xet
    03de6ea1dfa5f6290c7362f7ecf05ac9e779b476aaa741664fb46be9ca2eee9e almost 2 years ago
  • openthaigpt1.5-14b-instruct.fp16.gguf
    29.5 GB
    xet
    e4d309d34b98a8876f306cd3212f7b130d4c4db7873671402bcad89e45e39081 almost 2 years ago