Text Generation
GGUF
English
code
coder
qwen2.5
qwen2.5-coder
llama-cpp
llama.cpp
ollama
code-generation
tool-calling
conversational
cpu-inference
small-language-model
offline
sakthai
house-of-sak
Eval Results (legacy)
Eval Results
Instructions to use Nanthasit/sakthai-coder-1.5b 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 Nanthasit/sakthai-coder-1.5b 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 Nanthasit/sakthai-coder-1.5b:Q4_K_M # Run inference directly in the terminal: llama cli -hf Nanthasit/sakthai-coder-1.5b:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Nanthasit/sakthai-coder-1.5b:Q4_K_M # Run inference directly in the terminal: llama cli -hf Nanthasit/sakthai-coder-1.5b: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 Nanthasit/sakthai-coder-1.5b:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Nanthasit/sakthai-coder-1.5b: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 Nanthasit/sakthai-coder-1.5b:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Nanthasit/sakthai-coder-1.5b:Q4_K_M
Use Docker
docker model run hf.co/Nanthasit/sakthai-coder-1.5b:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use Nanthasit/sakthai-coder-1.5b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Nanthasit/sakthai-coder-1.5b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Nanthasit/sakthai-coder-1.5b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Nanthasit/sakthai-coder-1.5b:Q4_K_M
- Ollama
How to use Nanthasit/sakthai-coder-1.5b with Ollama:
ollama run hf.co/Nanthasit/sakthai-coder-1.5b:Q4_K_M
- Unsloth Desktop
- Pi
How to use Nanthasit/sakthai-coder-1.5b with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Nanthasit/sakthai-coder-1.5b:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "Nanthasit/sakthai-coder-1.5b:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use Nanthasit/sakthai-coder-1.5b with Docker Model Runner:
docker model run hf.co/Nanthasit/sakthai-coder-1.5b:Q4_K_M
- Lemonade
How to use Nanthasit/sakthai-coder-1.5b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Nanthasit/sakthai-coder-1.5b:Q4_K_M
Run and chat with the model
lemonade run user.sakthai-coder-1.5b-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use Nanthasit/sakthai-coder-1.5b with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Nanthasit/sakthai-coder-1.5b:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default Nanthasit/sakthai-coder-1.5b:Q4_K_M
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Nanthasit/sakthai-coder-1.5b with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Nanthasit/sakthai-coder-1.5b:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "Nanthasit/sakthai-coder-1.5b:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Download .venv/bin/activate from Nanthasit/sakthai-coder-1.5b: direct link, hf CLI and curl.
- Browser
- Download file 4.11 kB
-
https://huggingface.co/Nanthasit/sakthai-coder-1.5b/resolve/69183551fb043fb077cd3e5935ed4617d5faf3b0/.venv/bin/activate
- Command line
-
hf download hf://Nanthasit/sakthai-coder-1.5b@69183551fb043fb077cd3e5935ed4617d5faf3b0/.venv/bin/activate
-
curl -L -o activate https://huggingface.co/Nanthasit/sakthai-coder-1.5b/resolve/69183551fb043fb077cd3e5935ed4617d5faf3b0/.venv/bin/activate
4.11 kB
| # Copyright (c) 2020-202x The virtualenv developers | |
| # | |
| # Permission is hereby granted, free of charge, to any person obtaining | |
| # a copy of this software and associated documentation files (the | |
| # "Software"), to deal in the Software without restriction, including | |
| # without limitation the rights to use, copy, modify, merge, publish, | |
| # distribute, sublicense, and/or sell copies of the Software, and to | |
| # permit persons to whom the Software is furnished to do so, subject to | |
| # the following conditions: | |
| # | |
| # The above copyright notice and this permission notice shall be | |
| # included in all copies or substantial portions of the Software. | |
| # | |
| # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, | |
| # EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF | |
| # MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND | |
| # NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE | |
| # LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION | |
| # OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION | |
| # WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. | |
| # This file must be used with "source bin/activate" *from bash* | |
| # you cannot run it directly | |
| if ! [ -z "${SCRIPT_PATH+_}" ] ; then | |
| _OLD_SCRIPT_PATH="$SCRIPT_PATH" | |
| fi | |
| # Get script path (only used if environment is relocatable). | |
| if [ -n "${BASH_VERSION:+x}" ] ; then | |
| SCRIPT_PATH="${BASH_SOURCE[0]}" | |
| if [ "$SCRIPT_PATH" = "$0" ]; then | |
| # Only bash has a reasonably robust check for source'dness. | |
| echo "You must source this script: \$ source $0" >&2 | |
| exit 33 | |
| fi | |
| elif [ -n "${ZSH_VERSION:+x}" ] ; then | |
| SCRIPT_PATH="${(%):-%x}" | |
| elif [ -n "${KSH_VERSION:+x}" ] ; then | |
| SCRIPT_PATH="${.sh.file}" | |
| fi | |
| deactivate () { | |
| unset -f pydoc >/dev/null 2>&1 || true | |
| # reset old environment variables | |
| # ! [ -z ${VAR+_} ] returns true if VAR is declared at all | |
| if ! [ -z "${_OLD_VIRTUAL_PATH:+_}" ] ; then | |
| PATH="$_OLD_VIRTUAL_PATH" | |
| export PATH | |
| unset _OLD_VIRTUAL_PATH | |
| fi | |
| if ! [ -z "${_OLD_VIRTUAL_PYTHONHOME+_}" ] ; then | |
| PYTHONHOME="$_OLD_VIRTUAL_PYTHONHOME" | |
| export PYTHONHOME | |
| unset _OLD_VIRTUAL_PYTHONHOME | |
| fi | |
| # The hash command must be called to get it to forget past | |
| # commands. Without forgetting past commands the $PATH changes | |
| # we made may not be respected | |
| hash -r 2>/dev/null | |
| if ! [ -z "${_OLD_VIRTUAL_PS1+_}" ] ; then | |
| PS1="$_OLD_VIRTUAL_PS1" | |
| export PS1 | |
| unset _OLD_VIRTUAL_PS1 | |
| fi | |
| unset VIRTUAL_ENV | |
| unset VIRTUAL_ENV_PROMPT | |
| if [ ! "${1-}" = "nondestructive" ] ; then | |
| # Self destruct! | |
| unset -f deactivate | |
| fi | |
| } | |
| # unset irrelevant variables | |
| deactivate nondestructive | |
| VIRTUAL_ENV='/opt/data/sakthai-skills-repo/.venv' | |
| if ([ "$OSTYPE" = "cygwin" ] || [ "$OSTYPE" = "msys" ]) && $(command -v cygpath &> /dev/null) ; then | |
| VIRTUAL_ENV=$(cygpath -u "$VIRTUAL_ENV") | |
| fi | |
| export VIRTUAL_ENV | |
| # Unset the `SCRIPT_PATH` variable, now that the `VIRTUAL_ENV` variable | |
| # has been set. This is important for relocatable environments. | |
| if ! [ -z "${_OLD_SCRIPT_PATH+_}" ] ; then | |
| SCRIPT_PATH="$_OLD_SCRIPT_PATH" | |
| export SCRIPT_PATH | |
| unset _OLD_SCRIPT_PATH | |
| else | |
| unset SCRIPT_PATH | |
| fi | |
| _OLD_VIRTUAL_PATH="$PATH" | |
| PATH="$VIRTUAL_ENV/bin:$PATH" | |
| export PATH | |
| if [ "xsakthai-agent" != x ] ; then | |
| VIRTUAL_ENV_PROMPT="sakthai-agent" | |
| else | |
| VIRTUAL_ENV_PROMPT=$(basename "$VIRTUAL_ENV") | |
| fi | |
| export VIRTUAL_ENV_PROMPT | |
| # unset PYTHONHOME if set | |
| if ! [ -z "${PYTHONHOME+_}" ] ; then | |
| _OLD_VIRTUAL_PYTHONHOME="$PYTHONHOME" | |
| unset PYTHONHOME | |
| fi | |
| if [ -z "${VIRTUAL_ENV_DISABLE_PROMPT-}" ] ; then | |
| _OLD_VIRTUAL_PS1="${PS1-}" | |
| PS1="(${VIRTUAL_ENV_PROMPT}) ${PS1-}" | |
| export PS1 | |
| fi | |
| # Make sure to unalias pydoc if it's already there | |
| alias pydoc 2>/dev/null >/dev/null && unalias pydoc || true | |
| pydoc () { | |
| python -m pydoc "$@" | |
| } | |
| # The hash command must be called to get it to forget past | |
| # commands. Without forgetting past commands the $PATH changes | |
| # we made may not be respected | |
| hash -r 2>/dev/null || true | |