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kurtpayne
/
skillscan-detector-v4

Text Generation
Safetensors
GGUF
English
qwen2
security
skillscan
prompt-injection
skill-file-analysis
llama-cpp
conversational
Model card Files Files and versions
xet
Community

Instructions to use kurtpayne/skillscan-detector-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • llama-cpp-python

    How to use kurtpayne/skillscan-detector-v4 with llama-cpp-python:

    # !pip install llama-cpp-python
    
    from llama_cpp import Llama
    
    llm = Llama.from_pretrained(
    	repo_id="kurtpayne/skillscan-detector-v4",
    	filename="skillscan-detector-v4-q4_k_m.gguf",
    )
    
    llm.create_chat_completion(
    	messages = [
    		{
    			"role": "user",
    			"content": "What is the capital of France?"
    		}
    	]
    )
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • llama.cpp

    How to use kurtpayne/skillscan-detector-v4 with llama.cpp:

    Install from brew
    brew install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama-server -hf kurtpayne/skillscan-detector-v4:Q4_K_M
    # Run inference directly in the terminal:
    llama-cli -hf kurtpayne/skillscan-detector-v4:Q4_K_M
    Install from WinGet (Windows)
    winget install llama.cpp
    # Start a local OpenAI-compatible server with a web UI:
    llama-server -hf kurtpayne/skillscan-detector-v4:Q4_K_M
    # Run inference directly in the terminal:
    llama-cli -hf kurtpayne/skillscan-detector-v4:Q4_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 kurtpayne/skillscan-detector-v4:Q4_K_M
    # Run inference directly in the terminal:
    ./llama-cli -hf kurtpayne/skillscan-detector-v4:Q4_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 kurtpayne/skillscan-detector-v4:Q4_K_M
    # Run inference directly in the terminal:
    ./build/bin/llama-cli -hf kurtpayne/skillscan-detector-v4:Q4_K_M
    Use Docker
    docker model run hf.co/kurtpayne/skillscan-detector-v4:Q4_K_M
  • LM Studio
  • Jan
  • vLLM

    How to use kurtpayne/skillscan-detector-v4 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "kurtpayne/skillscan-detector-v4"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/chat/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "kurtpayne/skillscan-detector-v4",
    		"messages": [
    			{
    				"role": "user",
    				"content": "What is the capital of France?"
    			}
    		]
    	}'
    Use Docker
    docker model run hf.co/kurtpayne/skillscan-detector-v4:Q4_K_M
  • Ollama

    How to use kurtpayne/skillscan-detector-v4 with Ollama:

    ollama run hf.co/kurtpayne/skillscan-detector-v4:Q4_K_M
  • Unsloth Studio new

    How to use kurtpayne/skillscan-detector-v4 with Unsloth Studio:

    Install Unsloth Studio (macOS, Linux, WSL)
    curl -fsSL https://unsloth.ai/install.sh | sh
    # Run unsloth studio
    unsloth studio -H 0.0.0.0 -p 8888
    # Then open http://localhost:8888 in your browser
    # Search for kurtpayne/skillscan-detector-v4 to start chatting
    Install Unsloth Studio (Windows)
    irm https://unsloth.ai/install.ps1 | iex
    # Run unsloth studio
    unsloth studio -H 0.0.0.0 -p 8888
    # Then open http://localhost:8888 in your browser
    # Search for kurtpayne/skillscan-detector-v4 to start chatting
    Using HuggingFace Spaces for Unsloth
    # No setup required
    # Open https://huggingface.co/spaces/unsloth/studio in your browser
    # Search for kurtpayne/skillscan-detector-v4 to start chatting
  • Pi new

    How to use kurtpayne/skillscan-detector-v4 with Pi:

    Start the llama.cpp server
    # Install llama.cpp:
    brew install llama.cpp
    # Start a local OpenAI-compatible server:
    llama-server -hf kurtpayne/skillscan-detector-v4:Q4_K_M
    Configure the model in Pi
    # Install Pi:
    npm install -g @mariozechner/pi-coding-agent
    # Add to ~/.pi/agent/models.json:
    {
      "providers": {
        "llama-cpp": {
          "baseUrl": "http://localhost:8080/v1",
          "api": "openai-completions",
          "apiKey": "none",
          "models": [
            {
              "id": "skillscan-detector-v4"
            }
          ]
        }
      }
    }
    Run Pi
    # Start Pi in your project directory:
    pi
  • Docker Model Runner

    How to use kurtpayne/skillscan-detector-v4 with Docker Model Runner:

    docker model run hf.co/kurtpayne/skillscan-detector-v4:Q4_K_M
  • Lemonade

    How to use kurtpayne/skillscan-detector-v4 with Lemonade:

    Pull the model
    # Download Lemonade from https://lemonade-server.ai/
    lemonade pull kurtpayne/skillscan-detector-v4:Q4_K_M
    Run and chat with the model
    lemonade run user.skillscan-detector-v4-Q4_K_M
    List all available models
    lemonade list
skillscan-detector-v4
4.09 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 13 commits
kurtpayne's picture
kurtpayne
v4.7: safetensors + tokenizer
12a38ca verified 18 days ago
  • .gitattributes
    1.64 kB
    Add GGUF Q4_K_M quantized model for CPU inference about 1 month ago
  • README.md
    9.03 kB
    Add model card with eval results and usage instructions about 1 month ago
  • added_tokens.json
    605 Bytes
    Generative detector v4: 20035 examples, 3 epochs about 1 month ago
  • chat_template.jinja
    2.51 kB
    Generative detector v4: 20035 examples, 3 epochs about 1 month ago
  • config.json
    1.55 kB
    Generative detector v4: 20035 examples, 3 epochs about 1 month ago
  • generation_config.json

    Pickle imports

    • No problematic imports detected

    What is a pickle import?

    15 Bytes
    v4.7: safetensors + tokenizer 18 days ago
  • merges.txt
    1.67 MB
    Generative detector v4: 20035 examples, 3 epochs about 1 month ago
  • model.safetensors
    3.09 GB
    xet
    v4.7: safetensors + tokenizer 18 days ago
  • skillscan-detector-v4-q4_k_m.gguf
    986 MB
    xet
    v4.7: +33pp canary-attack catch rate, 98.8% verdict, 0/38 canary-benign FPs 18 days ago
  • special_tokens_map.json
    614 Bytes
    Generative detector v4: 20035 examples, 3 epochs about 1 month ago
  • tokenizer.json
    11.4 MB
    xet
    Generative detector v4: 20035 examples, 3 epochs about 1 month ago
  • tokenizer_config.json
    7.36 kB
    Generative detector v4: 20035 examples, 3 epochs about 1 month ago
  • vocab.json
    2.78 MB
    Generative detector v4: 20035 examples, 3 epochs about 1 month ago