Instructions to use AJKADZ/PHI_CODER 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 AJKADZ/PHI_CODER 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 AJKADZ/PHI_CODER:Q4_K_M # Run inference directly in the terminal: llama cli -hf AJKADZ/PHI_CODER:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf AJKADZ/PHI_CODER:Q4_K_M # Run inference directly in the terminal: llama cli -hf AJKADZ/PHI_CODER: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 AJKADZ/PHI_CODER:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf AJKADZ/PHI_CODER: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 AJKADZ/PHI_CODER:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf AJKADZ/PHI_CODER:Q4_K_M
Use Docker
docker model run hf.co/AJKADZ/PHI_CODER:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use AJKADZ/PHI_CODER with Ollama:
ollama run hf.co/AJKADZ/PHI_CODER:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use AJKADZ/PHI_CODER with Docker Model Runner:
docker model run hf.co/AJKADZ/PHI_CODER:Q4_K_M
- Lemonade
How to use AJKADZ/PHI_CODER with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull AJKADZ/PHI_CODER:Q4_K_M
Run and chat with the model
lemonade run user.PHI_CODER-Q4_K_M
List all available models
lemonade list
- Atomic Chat
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Download phi-coder-hf/llama.cpp/tools/run/README.md from AJKADZ/PHI_CODER: direct link, hf CLI and curl.
- Browser
- Download file 1.78 kB
-
https://huggingface.co/AJKADZ/PHI_CODER/resolve/main/phi-coder-hf/llama.cpp/tools/run/README.md
- Command line
-
hf download hf://AJKADZ/PHI_CODER/phi-coder-hf/llama.cpp/tools/run/README.md
-
curl -L -o README.md https://huggingface.co/AJKADZ/PHI_CODER/resolve/main/phi-coder-hf/llama.cpp/tools/run/README.md
1.78 kB
| # llama.cpp/example/run | |
| The purpose of this example is to demonstrate a minimal usage of llama.cpp for running models. | |
| ```bash | |
| llama-run granite3-moe | |
| ``` | |
| ```bash | |
| Description: | |
| Runs a llm | |
| Usage: | |
| llama-run [options] model [prompt] | |
| Options: | |
| -c, --context-size <value> | |
| Context size (default: 2048) | |
| -n, -ngl, --ngl <value> | |
| Number of GPU layers (default: 0) | |
| --temp <value> | |
| Temperature (default: 0.8) | |
| -v, --verbose, --log-verbose | |
| Set verbosity level to infinity (i.e. log all messages, useful for debugging) | |
| -h, --help | |
| Show help message | |
| Commands: | |
| model | |
| Model is a string with an optional prefix of | |
| huggingface:// (hf://), ollama://, https:// or file://. | |
| If no protocol is specified and a file exists in the specified | |
| path, file:// is assumed, otherwise if a file does not exist in | |
| the specified path, ollama:// is assumed. Models that are being | |
| pulled are downloaded with .partial extension while being | |
| downloaded and then renamed as the file without the .partial | |
| extension when complete. | |
| Examples: | |
| llama-run llama3 | |
| llama-run ollama://granite-code | |
| llama-run ollama://smollm:135m | |
| llama-run hf://QuantFactory/SmolLM-135M-GGUF/SmolLM-135M.Q2_K.gguf | |
| llama-run huggingface://bartowski/SmolLM-1.7B-Instruct-v0.2-GGUF/SmolLM-1.7B-Instruct-v0.2-IQ3_M.gguf | |
| llama-run ms://QuantFactory/SmolLM-135M-GGUF/SmolLM-135M.Q2_K.gguf | |
| llama-run modelscope://bartowski/SmolLM-1.7B-Instruct-v0.2-GGUF/SmolLM-1.7B-Instruct-v0.2-IQ3_M.gguf | |
| llama-run https://example.com/some-file1.gguf | |
| llama-run some-file2.gguf | |
| llama-run file://some-file3.gguf | |
| llama-run --ngl 999 some-file4.gguf | |
| llama-run --ngl 999 some-file5.gguf Hello World | |
| ``` | |