Instructions to use theprint/Coma-3B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use theprint/Coma-3B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="theprint/Coma-3B-GGUF",
	filename="coma-3b-f16.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 theprint/Coma-3B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf theprint/Coma-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf theprint/Coma-3B-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf theprint/Coma-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf theprint/Coma-3B-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 theprint/Coma-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf theprint/Coma-3B-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 theprint/Coma-3B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf theprint/Coma-3B-GGUF:Q4_K_M

Use Docker

docker model run hf.co/theprint/Coma-3B-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use theprint/Coma-3B-GGUF with Ollama:
```
ollama run hf.co/theprint/Coma-3B-GGUF:Q4_K_M
```

Unsloth Studio new

How to use theprint/Coma-3B-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 theprint/Coma-3B-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 theprint/Coma-3B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for theprint/Coma-3B-GGUF to start chatting

Pi new

How to use theprint/Coma-3B-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf theprint/Coma-3B-GGUF:Q4_K_M

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": "theprint/Coma-3B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use theprint/Coma-3B-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 theprint/Coma-3B-GGUF:Q4_K_M

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 theprint/Coma-3B-GGUF:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use theprint/Coma-3B-GGUF with Docker Model Runner:
```
docker model run hf.co/theprint/Coma-3B-GGUF:Q4_K_M
```

Lemonade

How to use theprint/Coma-3B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull theprint/Coma-3B-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Coma-3B-GGUF-Q4_K_M

List all available models

lemonade list

Coma 3B

Coma is based on Qwen 2.5 3B, GRPO-fine tuned on the natural reasoning data set from Meta.

Testing

The following system prompt was used in testing of the model:

Between the tags <think> and </think>: You will first think through your answer carefully step by step, including any potential risks or pit falls, the context of the user's request, and how best to present this. These are notes for yourself, so be detailed and honest in your assessment.

When you are done with the analysis, you must use your own guidelines from the previous section to construct the final response. The user will only see this section.

In summary, respond using this pattern:
<think>
  First, ...
</think>
  [your response]

Testing was done at temperature=1.0, top_k=45 and top_p=0.95.

Developed by: theprint
License: apache-2.0

Downloads last month: 27

GGUF

Model size

3B params

Architecture

qwen2

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Inference Providers NEW

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Model tree for theprint/Coma-3B-GGUF

Base model

theprint/Coma-3B

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Dataset used to train theprint/Coma-3B-GGUF