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ivanfioravanti
/
Qwen3.8-Flash-Next-DS4-IQ2

Image-Text-to-Text
GGUF
ds4
apple-metal
quantized
qwen
imatrix
conversational
Model card Files Files and versions
xet
Community
7

Instructions to use ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2 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 ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2 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 ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2
    # Run inference directly in the terminal:
    llama cli -hf ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2
    # Run inference directly in the terminal:
    llama cli -hf ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2
    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 ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2
    # Run inference directly in the terminal:
    ./llama-cli -hf ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2
    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 ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2
    Use Docker
    docker model run hf.co/ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2
  • LM Studio
  • Jan
  • vLLM

    How to use ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2",
    		"messages": [
    			{
    				"role": "user",
    				"content": [
    					{
    						"type": "text",
    						"text": "Describe this image in one sentence."
    					},
    					{
    						"type": "image_url",
    						"image_url": {
    							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
    						}
    					}
    				]
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2
  • Ollama

    How to use ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2 with Ollama:

    ollama run hf.co/ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2
  • Unsloth Desktop
  • Pi

    How to use ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2 with Pi:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2
    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": "ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Docker Model Runner

    How to use ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2 with Docker Model Runner:

    docker model run hf.co/ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2
  • Lemonade

    How to use ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2 with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2
    Run and chat with the model
    lemonade run user.Qwen3.8-Flash-Next-DS4-IQ2-{{QUANT_TAG}}
    List all available models
    lemonade list
  • Hermes Agent

    How to use ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2 with Hermes Agent:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2
    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 ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2
    Run Hermes
    hermes
  • Atomic Chat
  • OpenClaw

    How to use ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2 with OpenClaw:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2
    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 "ivanfioravanti/Qwen3.8-Flash-Next-DS4-IQ2" \
      --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"
Qwen3.8-Flash-Next-DS4-IQ2
44.8 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
ivanfioravanti's picture
ivanfioravanti
Replace IQ2 release with smaller padded Q2_K down model
b8b2039 verified about 1 month ago
  • .gitattributes
    1.7 kB
    Replace IQ2 release with smaller padded Q2_K down model about 1 month ago
  • LICENSE
    3.24 kB
    Publish calibrated IQ2 MTP model with quality and memory results about 1 month ago
  • Qwen3.8-Flash-Next-IQ2XXSImatrix-Q2KDownPad768-MTP.gguf
    44.8 GB
    xet
    Replace IQ2 release with smaller padded Q2_K down model about 1 month ago
  • Qwen3.8-Flash-Next-IQ2XXSImatrix-Q2KDownPad768-MTP.gguf.json
    261 kB
    Replace IQ2 release with smaller padded Q2_K down model about 1 month ago
  • README.md
    7.14 kB
    Replace IQ2 release with smaller padded Q2_K down model about 1 month ago
  • SHA256SUMS
    575 Bytes
    Replace IQ2 release with smaller padded Q2_K down model about 1 month ago
  • qwen38-q2down-results.json
    19.4 kB
    Replace IQ2 release with smaller padded Q2_K down model about 1 month ago
  • qwen38-q2down.md
    4.81 kB
    Replace IQ2 release with smaller padded Q2_K down model about 1 month ago