Instructions to use srisree/nano_coder_GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use srisree/nano_coder_GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="srisree/nano_coder_GGUF", filename="nano_coder.Q8_0.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 srisree/nano_coder_GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf srisree/nano_coder_GGUF:Q8_0 # Run inference directly in the terminal: llama-cli -hf srisree/nano_coder_GGUF:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf srisree/nano_coder_GGUF:Q8_0 # Run inference directly in the terminal: llama-cli -hf srisree/nano_coder_GGUF:Q8_0
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 srisree/nano_coder_GGUF:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf srisree/nano_coder_GGUF:Q8_0
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 srisree/nano_coder_GGUF:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf srisree/nano_coder_GGUF:Q8_0
Use Docker
docker model run hf.co/srisree/nano_coder_GGUF:Q8_0
- LM Studio
- Jan
- Ollama
How to use srisree/nano_coder_GGUF with Ollama:
ollama run hf.co/srisree/nano_coder_GGUF:Q8_0
- Unsloth Studio new
How to use srisree/nano_coder_GGUF 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 srisree/nano_coder_GGUF 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 srisree/nano_coder_GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for srisree/nano_coder_GGUF to start chatting
- Pi new
How to use srisree/nano_coder_GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf srisree/nano_coder_GGUF:Q8_0
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "srisree/nano_coder_GGUF:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use srisree/nano_coder_GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf srisree/nano_coder_GGUF:Q8_0
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 srisree/nano_coder_GGUF:Q8_0
Run Hermes
hermes
- Docker Model Runner
How to use srisree/nano_coder_GGUF with Docker Model Runner:
docker model run hf.co/srisree/nano_coder_GGUF:Q8_0
- Lemonade
How to use srisree/nano_coder_GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull srisree/nano_coder_GGUF:Q8_0
Run and chat with the model
lemonade run user.nano_coder_GGUF-Q8_0
List all available models
lemonade list
Do you plan to release variants of NanoCoder for other programming languages
Do you plan to release variants of NanoCoder for other programming languages or development environments, such as Python, C++, etc? That would make Nano Coder a very unique LLM. Users can use different variants at the same time or as needed each specializing in their own programming language or development environment. Theoretically it would turn a 1 trillion parameter LLM into a bunch of 1b parameters LLM. I don't know how any of this works and I can't train anything myself due to resource constraints but that's how I envision things.