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/docs/android.md from AJKADZ/PHI_CODER: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/AJKADZ/PHI_CODER/resolve/main/phi-coder-hf/llama.cpp/docs/android.md
- Command line
-
hf download hf://AJKADZ/PHI_CODER/phi-coder-hf/llama.cpp/docs/android.md
-
curl -L -o android.md https://huggingface.co/AJKADZ/PHI_CODER/resolve/main/phi-coder-hf/llama.cpp/docs/android.md
3.96 kB
| # Android | |
| ## Build on Android using Termux | |
| [Termux](https://termux.dev/en/) is an Android terminal emulator and Linux environment app (no root required). As of writing, Termux is available experimentally in the Google Play Store; otherwise, it may be obtained directly from the project repo or on F-Droid. | |
| With Termux, you can install and run `llama.cpp` as if the environment were Linux. Once in the Termux shell: | |
| ``` | |
| $ apt update && apt upgrade -y | |
| $ apt install git cmake | |
| ``` | |
| Then, follow the [build instructions](https://github.com/ggml-org/llama.cpp/blob/master/docs/build.md), specifically for CMake. | |
| Once the binaries are built, download your model of choice (e.g., from Hugging Face). It's recommended to place it in the `~/` directory for best performance: | |
| ``` | |
| $ curl -L {model-url} -o ~/{model}.gguf | |
| ``` | |
| Then, if you are not already in the repo directory, `cd` into `llama.cpp` and: | |
| ``` | |
| $ ./build/bin/llama-cli -m ~/{model}.gguf -c {context-size} -p "{your-prompt}" | |
| ``` | |
| Here, we show `llama-cli`, but any of the executables under `examples` should work, in theory. Be sure to set `context-size` to a reasonable number (say, 4096) to start with; otherwise, memory could spike and kill your terminal. | |
| To see what it might look like visually, here's an old demo of an interactive session running on a Pixel 5 phone: | |
| https://user-images.githubusercontent.com/271616/225014776-1d567049-ad71-4ef2-b050-55b0b3b9274c.mp4 | |
| ## Cross-compile using Android NDK | |
| It's possible to build `llama.cpp` for Android on your host system via CMake and the Android NDK. If you are interested in this path, ensure you already have an environment prepared to cross-compile programs for Android (i.e., install the Android SDK). Note that, unlike desktop environments, the Android environment ships with a limited set of native libraries, and so only those libraries are available to CMake when building with the Android NDK (see: https://developer.android.com/ndk/guides/stable_apis.) | |
| Once you're ready and have cloned `llama.cpp`, invoke the following in the project directory: | |
| ``` | |
| $ cmake \ | |
| -DCMAKE_TOOLCHAIN_FILE=$ANDROID_NDK/build/cmake/android.toolchain.cmake \ | |
| -DANDROID_ABI=arm64-v8a \ | |
| -DANDROID_PLATFORM=android-28 \ | |
| -DCMAKE_C_FLAGS="-march=armv8.7a" \ | |
| -DCMAKE_CXX_FLAGS="-march=armv8.7a" \ | |
| -DGGML_OPENMP=OFF \ | |
| -DGGML_LLAMAFILE=OFF \ | |
| -B build-android | |
| ``` | |
| Notes: | |
| - While later versions of Android NDK ship with OpenMP, it must still be installed by CMake as a dependency, which is not supported at this time | |
| - `llamafile` does not appear to support Android devices (see: https://github.com/Mozilla-Ocho/llamafile/issues/325) | |
| The above command should configure `llama.cpp` with the most performant options for modern devices. Even if your device is not running `armv8.7a`, `llama.cpp` includes runtime checks for available CPU features it can use. | |
| Feel free to adjust the Android ABI for your target. Once the project is configured: | |
| ``` | |
| $ cmake --build build-android --config Release -j{n} | |
| $ cmake --install build-android --prefix {install-dir} --config Release | |
| ``` | |
| After installing, go ahead and download the model of your choice to your host system. Then: | |
| ``` | |
| $ adb shell "mkdir /data/local/tmp/llama.cpp" | |
| $ adb push {install-dir} /data/local/tmp/llama.cpp/ | |
| $ adb push {model}.gguf /data/local/tmp/llama.cpp/ | |
| $ adb shell | |
| ``` | |
| In the `adb shell`: | |
| ``` | |
| $ cd /data/local/tmp/llama.cpp | |
| $ LD_LIBRARY_PATH=lib ./bin/llama-simple -m {model}.gguf -c {context-size} -p "{your-prompt}" | |
| ``` | |
| That's it! | |
| Be aware that Android will not find the library path `lib` on its own, so we must specify `LD_LIBRARY_PATH` in order to run the installed executables. Android does support `RPATH` in later API levels, so this could change in the future. Refer to the previous section for information about `context-size` (very important!) and running other `examples`. | |