Instructions to use smcleod/llama-3-1-8b-smcleod-golang-coder-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use smcleod/llama-3-1-8b-smcleod-golang-coder-v3 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="smcleod/llama-3-1-8b-smcleod-golang-coder-v3",
	filename="llama-3-1-8b-smcleod-golang-coder-v3.etf16-Q8_0.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use smcleod/llama-3-1-8b-smcleod-golang-coder-v3 with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf smcleod/llama-3-1-8b-smcleod-golang-coder-v3:Q8_0
# Run inference directly in the terminal:
llama-cli -hf smcleod/llama-3-1-8b-smcleod-golang-coder-v3:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf smcleod/llama-3-1-8b-smcleod-golang-coder-v3:Q8_0
# Run inference directly in the terminal:
llama-cli -hf smcleod/llama-3-1-8b-smcleod-golang-coder-v3: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 smcleod/llama-3-1-8b-smcleod-golang-coder-v3:Q8_0
# Run inference directly in the terminal:
./llama-cli -hf smcleod/llama-3-1-8b-smcleod-golang-coder-v3: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 smcleod/llama-3-1-8b-smcleod-golang-coder-v3:Q8_0
# Run inference directly in the terminal:
./build/bin/llama-cli -hf smcleod/llama-3-1-8b-smcleod-golang-coder-v3:Q8_0

Use Docker

docker model run hf.co/smcleod/llama-3-1-8b-smcleod-golang-coder-v3:Q8_0

LM Studio
Jan
Ollama
How to use smcleod/llama-3-1-8b-smcleod-golang-coder-v3 with Ollama:
```
ollama run hf.co/smcleod/llama-3-1-8b-smcleod-golang-coder-v3:Q8_0
```

Unsloth Studio

How to use smcleod/llama-3-1-8b-smcleod-golang-coder-v3 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 smcleod/llama-3-1-8b-smcleod-golang-coder-v3 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 smcleod/llama-3-1-8b-smcleod-golang-coder-v3 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for smcleod/llama-3-1-8b-smcleod-golang-coder-v3 to start chatting

How to use smcleod/llama-3-1-8b-smcleod-golang-coder-v3 with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf smcleod/llama-3-1-8b-smcleod-golang-coder-v3: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": "smcleod/llama-3-1-8b-smcleod-golang-coder-v3:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use smcleod/llama-3-1-8b-smcleod-golang-coder-v3 with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf smcleod/llama-3-1-8b-smcleod-golang-coder-v3: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 smcleod/llama-3-1-8b-smcleod-golang-coder-v3:Q8_0

Run Hermes

hermes

Docker Model Runner
How to use smcleod/llama-3-1-8b-smcleod-golang-coder-v3 with Docker Model Runner:
```
docker model run hf.co/smcleod/llama-3-1-8b-smcleod-golang-coder-v3:Q8_0
```

Lemonade

How to use smcleod/llama-3-1-8b-smcleod-golang-coder-v3 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull smcleod/llama-3-1-8b-smcleod-golang-coder-v3:Q8_0

Run and chat with the model

lemonade run user.llama-3-1-8b-smcleod-golang-coder-v3-Q8_0

List all available models

lemonade list

Llama 3.1 8b Golang Coder v3

This model has been trained on Golang style guides, best practices and code examples. This should (hopefully) make it quite capable with Golang coding tasks.

LoRA

FP16
BF16

GGUF

Q8_0 (with f16 embeddings): https://huggingface.co/smcleod/llama-3-1-8b-smcleod-golang-coder-v3/blob/main/llama-3-1-8b-smcleod-golang-coder-v2.etf16-Q8_0.gguf

Ollama

https://ollama.com/sammcj/llama-3-1-8b-smcleod-golang-coder-v3

Training

I trained this model (based on Llama 3.1 8b) on a merged dataset I created consisting of 50,627 rows, 13.3M input tokens and 2.2M output tokens. The total training consisted of 1,020,719 input tokens and 445,810 output tokens from 45,565 items in the dataset.

The dataset I created for this consists of multiple golang/programming focused datasets cleaned and merged and my own synthetically generated dataset based on several open source golang coding guides.

Downloads last month: 119

GGUF

Model size

8B params

Architecture

llama

Hardware compatibility

8-bit

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

smcleod
/

llama-3-1-8b-smcleod-golang-coder-v3

Llama 3.1 8b Golang Coder v3

LoRA

GGUF

Ollama

Training

Datasets used to train smcleod/llama-3-1-8b-smcleod-golang-coder-v3