Text Generation
GGUF
Rust
English
ruvllm
agent-routing
claude-code
recursive-language-model
embeddings
llm-inference
sona
hnsw
simd
imatrix
conversational
Instructions to use Princess3/Hpp 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 Princess3/Hpp 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 Princess3/Hpp:Q4_K_M # Run inference directly in the terminal: llama cli -hf Princess3/Hpp:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Princess3/Hpp:Q4_K_M # Run inference directly in the terminal: llama cli -hf Princess3/Hpp: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 Princess3/Hpp:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Princess3/Hpp: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 Princess3/Hpp:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Princess3/Hpp:Q4_K_M
Use Docker
docker model run hf.co/Princess3/Hpp:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use Princess3/Hpp with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Princess3/Hpp" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Princess3/Hpp", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Princess3/Hpp:Q4_K_M
- Ollama
How to use Princess3/Hpp with Ollama:
ollama run hf.co/Princess3/Hpp:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use Princess3/Hpp with Docker Model Runner:
docker model run hf.co/Princess3/Hpp:Q4_K_M
- Lemonade
How to use Princess3/Hpp with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Princess3/Hpp:Q4_K_M
Run and chat with the model
lemonade run user.Hpp-Q4_K_M
List all available models
lemonade list
- Atomic Chat
File size: 716 Bytes
51c3ba6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | {
"version": "2.3",
"release_date": "2026-01-20",
"sota_metrics": {
"total_triplets": 1078,
"hard_negative_ratio": 0.484,
"embedding_accuracy": 0.882,
"hard_negative_accuracy": 0.812,
"hybrid_routing_accuracy": 1.0,
"agent_types_supported": 13
},
"training_config": {
"epochs": 30,
"batch_size": 32,
"learning_rate": 2e-05,
"loss": "triplet + infonce",
"margin": 0.5,
"temperature": 0.07
},
"improvements": [
"500+ Claude-generated hard negatives (up from 100)",
"48% hard negative ratio (up from 18%)",
"Real Candle training with gradient updates",
"GRPO feedback loop with Claude-as-judge",
"GGUF adapter export for llama.cpp"
]
} |