Instructions to use hongyongjiang/python-reference-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use hongyongjiang/python-reference-models with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="hongyongjiang/python-reference-models", filename="gemma-3-4b-it_bin/gemma-3-4b-it-f16.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use hongyongjiang/python-reference-models 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 hongyongjiang/python-reference-models:F16 # Run inference directly in the terminal: llama cli -hf hongyongjiang/python-reference-models:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf hongyongjiang/python-reference-models:F16 # Run inference directly in the terminal: llama cli -hf hongyongjiang/python-reference-models:F16
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 hongyongjiang/python-reference-models:F16 # Run inference directly in the terminal: ./llama-cli -hf hongyongjiang/python-reference-models:F16
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 hongyongjiang/python-reference-models:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf hongyongjiang/python-reference-models:F16
Use Docker
docker model run hf.co/hongyongjiang/python-reference-models:F16
- LM Studio
- Jan
- Ollama
How to use hongyongjiang/python-reference-models with Ollama:
ollama run hf.co/hongyongjiang/python-reference-models:F16
- Unsloth Studio
How to use hongyongjiang/python-reference-models 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 hongyongjiang/python-reference-models 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 hongyongjiang/python-reference-models to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for hongyongjiang/python-reference-models to start chatting
- Atomic Chat new
- Docker Model Runner
How to use hongyongjiang/python-reference-models with Docker Model Runner:
docker model run hf.co/hongyongjiang/python-reference-models:F16
- Lemonade
How to use hongyongjiang/python-reference-models with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull hongyongjiang/python-reference-models:F16
Run and chat with the model
lemonade run user.python-reference-models-F16
List all available models
lemonade list
Upload folder using huggingface_hub
Browse files- .gitattributes +1 -0
- llama3.2-1b_bin/Llama-3.2-1B-Instruct-f16.gguf +3 -0
- llama3.2-1b_bin/layer_0.bin +3 -0
- llama3.2-1b_bin/layer_1.bin +3 -0
- llama3.2-1b_bin/layer_10.bin +3 -0
- llama3.2-1b_bin/layer_11.bin +3 -0
- llama3.2-1b_bin/layer_12.bin +3 -0
- llama3.2-1b_bin/layer_13.bin +3 -0
- llama3.2-1b_bin/layer_14.bin +3 -0
- llama3.2-1b_bin/layer_15.bin +3 -0
- llama3.2-1b_bin/layer_2.bin +3 -0
- llama3.2-1b_bin/layer_3.bin +3 -0
- llama3.2-1b_bin/layer_4.bin +3 -0
- llama3.2-1b_bin/layer_5.bin +3 -0
- llama3.2-1b_bin/layer_6.bin +3 -0
- llama3.2-1b_bin/layer_7.bin +3 -0
- llama3.2-1b_bin/layer_8.bin +3 -0
- llama3.2-1b_bin/layer_9.bin +3 -0
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