Instructions to use lerugray/the-basel-program-7b 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 lerugray/the-basel-program-7b 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 lerugray/the-basel-program-7b:Q5_K_M # Run inference directly in the terminal: llama cli -hf lerugray/the-basel-program-7b:Q5_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf lerugray/the-basel-program-7b:Q5_K_M # Run inference directly in the terminal: llama cli -hf lerugray/the-basel-program-7b:Q5_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 lerugray/the-basel-program-7b:Q5_K_M # Run inference directly in the terminal: ./llama-cli -hf lerugray/the-basel-program-7b:Q5_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 lerugray/the-basel-program-7b:Q5_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf lerugray/the-basel-program-7b:Q5_K_M
Use Docker
docker model run hf.co/lerugray/the-basel-program-7b:Q5_K_M
- LM Studio
- Jan
- vLLM
How to use lerugray/the-basel-program-7b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "lerugray/the-basel-program-7b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lerugray/the-basel-program-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/lerugray/the-basel-program-7b:Q5_K_M
- Ollama
How to use lerugray/the-basel-program-7b with Ollama:
ollama run hf.co/lerugray/the-basel-program-7b:Q5_K_M
- Unsloth Desktop
- Docker Model Runner
How to use lerugray/the-basel-program-7b with Docker Model Runner:
docker model run hf.co/lerugray/the-basel-program-7b:Q5_K_M
- Lemonade
How to use lerugray/the-basel-program-7b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull lerugray/the-basel-program-7b:Q5_K_M
Run and chat with the model
lemonade run user.the-basel-program-7b-Q5_K_M
List all available models
lemonade list
- Atomic Chat
Download Modelfile.the-basel-program from lerugray/the-basel-program-7b: direct link, hf CLI and curl.
- Browser
- Download file 383 Bytes
-
https://huggingface.co/lerugray/the-basel-program-7b/resolve/main/Modelfile.the-basel-program
- Command line
-
hf download hf://lerugray/the-basel-program-7b/Modelfile.the-basel-program
-
curl -L -o Modelfile.the-basel-program https://huggingface.co/lerugray/the-basel-program-7b/resolve/main/Modelfile.the-basel-program
383 Bytes
| FROM ./the-basel-program-7b-Q5_K_M.gguf | |
| TEMPLATE """A visitor comes to Theodor Herzl's study and puts this question to him: {{ .Prompt }} | |
| Herzl sets down his pen, considers a moment, and answers in his own voice -- plainly, sequentially, without rhetorical performance: | |
| """ | |
| PARAMETER temperature 0.75 | |
| PARAMETER top_p 0.9 | |
| PARAMETER num_predict 320 | |
| PARAMETER stop "A visitor comes" | |