Instructions to use Myrall/turtle-llama-3-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use Myrall/turtle-llama-3-gguf 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 Myrall/turtle-llama-3-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Myrall/turtle-llama-3-gguf:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Myrall/turtle-llama-3-gguf:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Myrall/turtle-llama-3-gguf: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 Myrall/turtle-llama-3-gguf:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Myrall/turtle-llama-3-gguf: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 Myrall/turtle-llama-3-gguf:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Myrall/turtle-llama-3-gguf:Q4_K_M

Use Docker

docker model run hf.co/Myrall/turtle-llama-3-gguf:Q4_K_M

Llama new
LM Studio
Jan

vLLM

How to use Myrall/turtle-llama-3-gguf with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Myrall/turtle-llama-3-gguf"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Myrall/turtle-llama-3-gguf",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Myrall/turtle-llama-3-gguf:Q4_K_M

Ollama
How to use Myrall/turtle-llama-3-gguf with Ollama:
```
ollama run hf.co/Myrall/turtle-llama-3-gguf:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use Myrall/turtle-llama-3-gguf with Docker Model Runner:
```
docker model run hf.co/Myrall/turtle-llama-3-gguf:Q4_K_M
```

Lemonade

How to use Myrall/turtle-llama-3-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Myrall/turtle-llama-3-gguf:Q4_K_M

Run and chat with the model

lemonade run user.turtle-llama-3-gguf-Q4_K_M

List all available models

lemonade list

Atomic Chat

🐢 Turtle Llama 3 (GGUF + Chat UI)

Update: This model now includes a local web interface! You can download the turtle-chat.html and Start.bat launcher from the GitHub Repository to chat with this model in a clean, ChatGPT-like environment.

This is a fine-tuned version of Llama 3 (8B), specialized in Herpetology (Turtle Care & Biology). It was trained using Unsloth and converted to GGUF format for efficient local inference.

💻 Source Code

The training dataset and inference scripts are available on GitHub: View GitHub Repository

How to Run

You can run this model using the llama-cpp-python library. See the GitHub repo for a full Python script.

Downloads last month: 13

GGUF

Model size

8B params

Architecture

llama

Hardware compatibility

4-bit