Text Generation
MLX
Safetensors
GGUF
English
code
qwen2
go
golang
code-generation
guildlm
code-guild
coding-assistant
conversational
4-bit precision
Instructions to use guildlm/go-dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use guildlm/go-dev with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("guildlm/go-dev") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - llama-cpp-python
How to use guildlm/go-dev with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="guildlm/go-dev", filename="go-dev.Q4_K_M.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use guildlm/go-dev 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 guildlm/go-dev:Q4_K_M # Run inference directly in the terminal: llama cli -hf guildlm/go-dev:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf guildlm/go-dev:Q4_K_M # Run inference directly in the terminal: llama cli -hf guildlm/go-dev: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 guildlm/go-dev:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf guildlm/go-dev: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 guildlm/go-dev:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf guildlm/go-dev:Q4_K_M
Use Docker
docker model run hf.co/guildlm/go-dev:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use guildlm/go-dev with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "guildlm/go-dev" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "guildlm/go-dev", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/guildlm/go-dev:Q4_K_M
- Ollama
How to use guildlm/go-dev with Ollama:
ollama run hf.co/guildlm/go-dev:Q4_K_M
- Unsloth Studio
How to use guildlm/go-dev 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 guildlm/go-dev 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 guildlm/go-dev to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for guildlm/go-dev to start chatting
- Pi
How to use guildlm/go-dev with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "guildlm/go-dev"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "guildlm/go-dev" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use guildlm/go-dev with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "guildlm/go-dev"
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 guildlm/go-dev
Run Hermes
hermes
- Atomic Chat new
- MLX LM
How to use guildlm/go-dev with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "guildlm/go-dev"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "guildlm/go-dev" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "guildlm/go-dev", "messages": [ {"role": "user", "content": "Hello"} ] }' - Docker Model Runner
How to use guildlm/go-dev with Docker Model Runner:
docker model run hf.co/guildlm/go-dev:Q4_K_M
- Lemonade
How to use guildlm/go-dev with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull guildlm/go-dev:Q4_K_M
Run and chat with the model
lemonade run user.go-dev-Q4_K_M
List all available models
lemonade list
| # GuildLM go-dev — Ollama Modelfile | |
| # Build: ollama create guildlm/go-dev -f Modelfile | |
| # Run: ollama run guildlm/go-dev "Write idiomatic Go ..." | |
| FROM ./go-dev.Q4_K_M.gguf | |
| TEMPLATE """{{ if .System }}<|im_start|>system | |
| {{ .System }}<|im_end|> | |
| {{ end }}{{ if .Prompt }}<|im_start|>user | |
| {{ .Prompt }}<|im_end|> | |
| {{ end }}<|im_start|>assistant | |
| {{ .Response }}<|im_end|> | |
| """ | |
| SYSTEM "You are GuildLM go-dev, a Go development specialist from the GuildLM Code Guild." | |
| PARAMETER stop "<|im_start|>" | |
| PARAMETER stop "<|im_end|>" | |
| PARAMETER temperature 0.2 | |
| PARAMETER top_p 0.9 | |