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
Download phi-coder-hf/llama.cpp/tests/test-tokenizer-0.sh from AJKADZ/PHI_CODER: direct link, hf CLI and curl.
- Browser
- Download file 970 Bytes
-
https://huggingface.co/AJKADZ/PHI_CODER/resolve/main/phi-coder-hf/llama.cpp/tests/test-tokenizer-0.sh
- Command line
-
hf download hf://AJKADZ/PHI_CODER/phi-coder-hf/llama.cpp/tests/test-tokenizer-0.sh
-
curl -L -o test-tokenizer-0.sh https://huggingface.co/AJKADZ/PHI_CODER/resolve/main/phi-coder-hf/llama.cpp/tests/test-tokenizer-0.sh
970 Bytes
| # | |
| # Usage: | |
| # | |
| # test-tokenizer-0.sh <name> <input> | |
| # | |
| if [ $# -ne 2 ]; then | |
| printf "Usage: $0 <name> <input>\n" | |
| exit 1 | |
| fi | |
| name=$1 | |
| input=$2 | |
| make -j tests/test-tokenizer-0 | |
| printf "Testing %s on %s ...\n" $name $input | |
| set -e | |
| printf "Tokenizing using (py) Python AutoTokenizer ...\n" | |
| python3 ./tests/test-tokenizer-0.py ./models/tokenizers/$name --fname-tok $input > /tmp/test-tokenizer-0-$name-py.log 2>&1 | |
| printf "Tokenizing using (cpp) llama.cpp ...\n" | |
| ./tests/test-tokenizer-0 ./models/ggml-vocab-$name.gguf $input > /tmp/test-tokenizer-0-$name-cpp.log 2>&1 | |
| cat /tmp/test-tokenizer-0-$name-py.log | grep "tokenized in" | |
| cat /tmp/test-tokenizer-0-$name-cpp.log | grep "tokenized in" | |
| set +e | |
| diff $input.tok $input.tokcpp > /dev/null 2>&1 | |
| if [ $? -eq 0 ]; then | |
| printf "Tokenization is correct!\n" | |
| else | |
| diff $input.tok $input.tokcpp | head -n 32 | |
| printf "Tokenization differs!\n" | |
| fi | |