Instructions to use CyberCoder225/maira-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use CyberCoder225/maira-model with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="CyberCoder225/maira-model", filename="SmolLM2-360M-Instruct.Q4_K_M.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use CyberCoder225/maira-model with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf CyberCoder225/maira-model:Q4_K_M # Run inference directly in the terminal: llama-cli -hf CyberCoder225/maira-model:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf CyberCoder225/maira-model:Q4_K_M # Run inference directly in the terminal: llama-cli -hf CyberCoder225/maira-model: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 CyberCoder225/maira-model:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf CyberCoder225/maira-model: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 CyberCoder225/maira-model:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf CyberCoder225/maira-model:Q4_K_M
Use Docker
docker model run hf.co/CyberCoder225/maira-model:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use CyberCoder225/maira-model with Ollama:
ollama run hf.co/CyberCoder225/maira-model:Q4_K_M
- Unsloth Studio
How to use CyberCoder225/maira-model with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for CyberCoder225/maira-model to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for CyberCoder225/maira-model to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for CyberCoder225/maira-model to start chatting
- Docker Model Runner
How to use CyberCoder225/maira-model with Docker Model Runner:
docker model run hf.co/CyberCoder225/maira-model:Q4_K_M
- Lemonade
How to use CyberCoder225/maira-model with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull CyberCoder225/maira-model:Q4_K_M
Run and chat with the model
lemonade run user.maira-model-Q4_K_M
List all available models
lemonade list
File size: 887 Bytes
8b94a51 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | FROM python:3.10-slim
# ---- HF-required environment ----
ENV PYTHONUNBUFFERED=1 \
PORT=7860
# ---- System deps ----
RUN apt-get update && apt-get install -y \
git \
build-essential \
curl \
&& rm -rf /var/lib/apt/lists/*
# ---- Create non-root user (MANDATORY for HF) ----
RUN useradd -m -u 1000 user
# ---- App directory ----
WORKDIR /home/user/app
# ---- Copy project files ----
COPY . .
# ---- Fix permissions ----
RUN chown -R user:user /home/user/app
# ---- Switch to non-root ----
USER user
# ---- Python deps (CPU-safe) ----
RUN pip install --no-cache-dir --upgrade pip && \
pip install --no-cache-dir \
fastapi \
uvicorn \
transformers \
sentencepiece \
llama-cpp-python \
psutil
# ---- HF ONLY exposes this port ----
EXPOSE 7860
# ---- RUN app.py (THIS IS THE FIX) ----
CMD ["python", "app.py"]
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