Instructions to use pythonstudentiam/tinyllm 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 pythonstudentiam/tinyllm 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 pythonstudentiam/tinyllm:F16 # Run inference directly in the terminal: llama cli -hf pythonstudentiam/tinyllm:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf pythonstudentiam/tinyllm:F16 # Run inference directly in the terminal: llama cli -hf pythonstudentiam/tinyllm: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 pythonstudentiam/tinyllm:F16 # Run inference directly in the terminal: ./llama-cli -hf pythonstudentiam/tinyllm: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 pythonstudentiam/tinyllm:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf pythonstudentiam/tinyllm:F16
Use Docker
docker model run hf.co/pythonstudentiam/tinyllm:F16
- LM Studio
- Jan
- vLLM
How to use pythonstudentiam/tinyllm with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "pythonstudentiam/tinyllm" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "pythonstudentiam/tinyllm", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/pythonstudentiam/tinyllm:F16
- Ollama
How to use pythonstudentiam/tinyllm with Ollama:
ollama run hf.co/pythonstudentiam/tinyllm:F16
- Unsloth Desktop
- Docker Model Runner
How to use pythonstudentiam/tinyllm with Docker Model Runner:
docker model run hf.co/pythonstudentiam/tinyllm:F16
- Lemonade
How to use pythonstudentiam/tinyllm with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull pythonstudentiam/tinyllm:F16
Run and chat with the model
lemonade run user.tinyllm-F16
List all available models
lemonade list
- Atomic Chat
Download model.safetensors from pythonstudentiam/tinyllm: direct link, hf CLI and curl.
- Browser
- Download file 62.9 MB
-
https://huggingface.co/pythonstudentiam/tinyllm/resolve/main/model.safetensors
- Command line
-
hf download hf://pythonstudentiam/tinyllm/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/pythonstudentiam/tinyllm/resolve/main/model.safetensors
62.9 MB
- Xet hash:
- 8554f992adc4eee0986750015ee08613c22c247e87ea857c130b7e643bed899a
- Size of remote file:
- 62.9 MB
- SHA256:
- cb1646ce3e70f0b72a5329948d8c02de5939999ef33fa322f29a5304387b700a
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