Instructions to use hongyongjiang/python-reference-models 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 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
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -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
- Llama new
- LM Studio
- Jan
- Ollama
How to use hongyongjiang/python-reference-models with Ollama:
ollama run hf.co/hongyongjiang/python-reference-models:F16
- Unsloth Desktop
- 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
- Atomic Chat
Download qwen2.5-vl-3b_bin/layer_35.bin from hongyongjiang/python-reference-models: direct link, hf CLI and curl.
- Browser
- Download file 77.2 MB
-
https://huggingface.co/hongyongjiang/python-reference-models/resolve/main/qwen2.5-vl-3b_bin/layer_35.bin
- Command line
-
hf download hf://hongyongjiang/python-reference-models/qwen2.5-vl-3b_bin/layer_35.bin
-
curl -L -o layer_35.bin https://huggingface.co/hongyongjiang/python-reference-models/resolve/main/qwen2.5-vl-3b_bin/layer_35.bin
77.2 MB
- Xet hash:
- 3c97ab082f980a4a603434f4a8ab2b01b9df2dbd75916ec51bd5834f7ab91168
- Size of remote file:
- 77.2 MB
- SHA256:
- 7dc5fc9276f22e59ea1bc17e694f902b55f9330414b141fad8fd28cdce7ecdeb
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