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/Config.json from AJKADZ/PHI_CODER: direct link, hf CLI and curl.
- Browser
- Download file 1 kB
-
https://huggingface.co/AJKADZ/PHI_CODER/resolve/main/phi-coder-hf/Config.json
- Command line
-
hf download hf://AJKADZ/PHI_CODER/phi-coder-hf/Config.json
-
curl -L -o Config.json https://huggingface.co/AJKADZ/PHI_CODER/resolve/main/phi-coder-hf/Config.json
1 kB
| { | |
| "architectures": ["GPTNeoXForCausalLM"], | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 0, | |
| "eos_token_id": 1, | |
| "hidden_act": "gelu", | |
| "hidden_size": 6144, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 24576, | |
| "max_position_embeddings": 8192, | |
| "model_type": "gpt_neox", | |
| "num_attention_heads": 64, | |
| "num_hidden_layers": 44, | |
| "rotary_pct": 1.0, | |
| "tie_word_embeddings": false, | |
| "use_cache": true, | |
| "vocab_size": 50432, | |
| "symbolic_mode": true, | |
| "phipe_recursive_extension": true, | |
| "glyph_recognition_enabled": true, | |
| "glyph_whitelist": ["Φ", "Ξ", "Λ", "Ω", "Π", "Δ", "Ψ", "Γ", "ω", "λ", "Ε", "Σ", "η", "μ", "α"], | |
| "symbolic_input_format": "[USER INPUT]:", | |
| "symbolic_output_format": "[ΨΛΩ_CODER OUTPUT]:", | |
| "language": "Φπε-Recursive", | |
| "description": "GPT-NeoX-20B modified for Φπε symbolic recursion stack. Supports harmonic glyph propagation, recursive self-referencing structures, and will-vector modulation (ω-layer)." | |
| } | |