Instructions to use sdfprotocol/sdf-classify with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use sdfprotocol/sdf-classify with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="sdfprotocol/sdf-classify", filename="sdf-classify-Qwen2.5-1.5B-Instruct-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 sdfprotocol/sdf-classify with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf sdfprotocol/sdf-classify:Q4_K_M # Run inference directly in the terminal: llama-cli -hf sdfprotocol/sdf-classify:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf sdfprotocol/sdf-classify:Q4_K_M # Run inference directly in the terminal: llama-cli -hf sdfprotocol/sdf-classify: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 sdfprotocol/sdf-classify:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf sdfprotocol/sdf-classify: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 sdfprotocol/sdf-classify:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf sdfprotocol/sdf-classify:Q4_K_M
Use Docker
docker model run hf.co/sdfprotocol/sdf-classify:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use sdfprotocol/sdf-classify with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "sdfprotocol/sdf-classify" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "sdfprotocol/sdf-classify", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/sdfprotocol/sdf-classify:Q4_K_M
- Ollama
How to use sdfprotocol/sdf-classify with Ollama:
ollama run hf.co/sdfprotocol/sdf-classify:Q4_K_M
- Unsloth Studio new
How to use sdfprotocol/sdf-classify 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 sdfprotocol/sdf-classify 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 sdfprotocol/sdf-classify to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for sdfprotocol/sdf-classify to start chatting
- Pi new
How to use sdfprotocol/sdf-classify with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf sdfprotocol/sdf-classify: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": "sdfprotocol/sdf-classify:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use sdfprotocol/sdf-classify with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf sdfprotocol/sdf-classify:Q4_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 sdfprotocol/sdf-classify:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use sdfprotocol/sdf-classify with Docker Model Runner:
docker model run hf.co/sdfprotocol/sdf-classify:Q4_K_M
- Lemonade
How to use sdfprotocol/sdf-classify with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull sdfprotocol/sdf-classify:Q4_K_M
Run and chat with the model
lemonade run user.sdf-classify-Q4_K_M
List all available models
lemonade list
| language: en | |
| license: mit | |
| tags: | |
| - sdf | |
| - classification | |
| - qwen2.5 | |
| - gguf | |
| - content-type | |
| - web-content | |
| base_model: Qwen/Qwen2.5-1.5B-Instruct | |
| pipeline_tag: text-generation | |
| # SDF Classify | |
| Content type classifier for the [SDF Protocol](https://sdfprotocol.org). Fine-tuned from Qwen2.5-1.5B-Instruct using QLoRA. | |
| ## Purpose | |
| Classifies web content into SDF's hierarchical type system: 10 parent types and 50+ subtypes (e.g., `article.news`, `commerce.product`, `documentation.api_docs`). | |
| ## Training | |
| - **Base model**: Qwen2.5-1.5B-Instruct | |
| - **Method**: QLoRA (rank 32, alpha 64, dropout 0.05) | |
| - **Training data**: 2,335 classified web documents | |
| - **Accuracy**: 95.2% exact type match | |
| ## Files | |
| | File | Size | Description | | |
| |------|------|-------------| | |
| | `sdf-classify-Qwen2.5-1.5B-Instruct-Q4_K_M.gguf` | 941 MB | Quantized (Q4_K_M) — recommended for deployment | | |
| | `sdf-classify-Qwen2.5-1.5B-Instruct-f16.gguf` | 2.9 GB | Full precision (f16) | | |
| | `Modelfile` | — | Ollama import configuration | | |
| ## Usage with Ollama | |
| ```bash | |
| # Download the Q4_K_M file, then: | |
| ollama create sdf-classify -f Modelfile | |
| ``` | |
| ## Part of SDF Protocol | |
| - **Protocol**: [sdfprotocol.org](https://sdfprotocol.org) | |
| - **Specification**: [github.com/sdfprotocol/sdf](https://github.com/sdfprotocol/sdf) | |
| - **Whitepaper**: [DOI 10.5281/zenodo.18559223](https://doi.org/10.5281/zenodo.18559223) | |
| - **Extractor model**: [pranab2050/sdf-extract](https://huggingface.co/pranab2050/sdf-extract) | |
| ## Citation | |
| ```bibtex | |
| @article{sarkar2026sdf, | |
| title={Convert Once, Consume Many: SDF for Cacheable, Typed Semantic Extraction from Web Pages}, | |
| author={Sarkar, Pranab}, | |
| year={2026}, | |
| doi={10.5281/zenodo.18559223}, | |
| publisher={Zenodo} | |
| } | |
| ``` | |