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mp-juuuns
/
qwen3.5-4l-vocab40k-en-ko-headless

Feature Extraction
Transformers
Safetensors
GGUF
English
Korean
qwen3_5_text
qwen3.5
backbone
headless
classification-backbone
knowledge-distillation
model-compression
vocabulary-pruning
korean
edge-ai
conversational
Model card Files Files and versions
xet
Community

Instructions to use mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    pipe(messages)
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless")
    model = AutoModel.from_pretrained("mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless", device_map="auto")
    messages = [
        {"role": "user", "content": "Who are you?"},
    ]
    inputs = tokenizer.apply_chat_template(
    	messages,
    	add_generation_prompt=True,
    	tokenize=True,
    	return_dict=True,
    	return_tensors="pt",
    ).to(model.device)
    
    outputs = model.generate(**inputs, max_new_tokens=40)
    print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • llama.cpp

    How to use mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless 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 mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless:Q8_0
    # Run inference directly in the terminal:
    llama cli -hf mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless:Q8_0
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama serve -hf mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless:Q8_0
    # Run inference directly in the terminal:
    llama cli -hf mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless:Q8_0
    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 mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless:Q8_0
    # Run inference directly in the terminal:
    ./llama-cli -hf mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless:Q8_0
    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 mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless:Q8_0
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless:Q8_0
    Use Docker
    docker model run hf.co/mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless:Q8_0
  • LM Studio
  • Jan
  • Ollama

    How to use mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless with Ollama:

    ollama run hf.co/mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless:Q8_0
  • Unsloth Desktop
  • Pi

    How to use mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless with Pi:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless:Q8_0
    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": "mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless:Q8_0"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Docker Model Runner

    How to use mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless with Docker Model Runner:

    docker model run hf.co/mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless:Q8_0
  • Lemonade

    How to use mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless:Q8_0
    Run and chat with the model
    lemonade run user.qwen3.5-4l-vocab40k-en-ko-headless-Q8_0
    List all available models
    lemonade list
  • Hermes Agent

    How to use mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless with Hermes Agent:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless:Q8_0
    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 mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless:Q8_0
    Run Hermes
    hermes
  • Atomic Chat
  • OpenClaw

    How to use mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless with OpenClaw:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama serve -hf mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless:Q8_0
    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 "mp-juuuns/qwen3.5-4l-vocab40k-en-ko-headless:Q8_0" \
      --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"
qwen3.5-4l-vocab40k-en-ko-headless / distillation
65.4 kB
Ctrl+K
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  • 1 contributor
History: 2 commits
mp-juuuns's picture
mp-juuuns
distillation: stop stamping a layer-map provenance the card says is false; refuse cut-vocabulary teachers
3a3eea4 verified 2 days ago
  • configs
    Publish task-agnostic 4L base, separate SemEval model, and 24L-to-4L distillation platform about 2 months ago
  • examples
    Publish task-agnostic 4L base, separate SemEval model, and 24L-to-4L distillation platform about 2 months ago
  • qwen35_distill
    distillation: stop stamping a layer-map provenance the card says is false; refuse cut-vocabulary teachers 2 days ago
  • README.md
    3.43 kB
    Publish task-agnostic 4L base, separate SemEval model, and 24L-to-4L distillation platform about 2 months ago
  • pyproject.toml
    487 Bytes
    Publish task-agnostic 4L base, separate SemEval model, and 24L-to-4L distillation platform about 2 months ago