Instructions to use Prevon/function-gemma-270m-it-full-ft-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 Prevon/function-gemma-270m-it-full-ft-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 Prevon/function-gemma-270m-it-full-ft-gguf:Q8_0
# Run inference directly in the terminal:
llama cli -hf Prevon/function-gemma-270m-it-full-ft-gguf:Q8_0

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Prevon/function-gemma-270m-it-full-ft-gguf:Q8_0
# Run inference directly in the terminal:
llama cli -hf Prevon/function-gemma-270m-it-full-ft-gguf:Q8_0

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf Prevon/function-gemma-270m-it-full-ft-gguf:Q8_0
# Run inference directly in the terminal:
./build/bin/llama cli -hf Prevon/function-gemma-270m-it-full-ft-gguf:Q8_0

Use Docker

docker model run hf.co/Prevon/function-gemma-270m-it-full-ft-gguf:Q8_0

Llama new
LM Studio
Jan
Ollama
How to use Prevon/function-gemma-270m-it-full-ft-gguf with Ollama:
```
ollama run hf.co/Prevon/function-gemma-270m-it-full-ft-gguf:Q8_0
```
Unsloth Desktop

How to use Prevon/function-gemma-270m-it-full-ft-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Prevon/function-gemma-270m-it-full-ft-gguf:Q8_0

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Prevon/function-gemma-270m-it-full-ft-gguf:Q8_0"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Prevon/function-gemma-270m-it-full-ft-gguf with Docker Model Runner:
```
docker model run hf.co/Prevon/function-gemma-270m-it-full-ft-gguf:Q8_0
```

Lemonade

How to use Prevon/function-gemma-270m-it-full-ft-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Prevon/function-gemma-270m-it-full-ft-gguf:Q8_0

Run and chat with the model

lemonade run user.function-gemma-270m-it-full-ft-gguf-Q8_0

List all available models

lemonade list

Hermes Agent

How to use Prevon/function-gemma-270m-it-full-ft-gguf with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Prevon/function-gemma-270m-it-full-ft-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 Prevon/function-gemma-270m-it-full-ft-gguf:Q8_0

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Prevon/function-gemma-270m-it-full-ft-gguf with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Prevon/function-gemma-270m-it-full-ft-gguf:Q8_0

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "Prevon/function-gemma-270m-it-full-ft-gguf:Q8_0" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

FunctionGemma 270M full fine-tune (GGUF, Q8_0)

This repository holds one file, functiongemma-270m-it-fullft-Q8_0.gguf: the llama.cpp (GGUF, 8-bit) conversion of the first Prevon Pulse fine-tune (PrevonFounder/prevon-pulse). The Prevon app uses it on Intel Macs through llama.cpp.

FunctionGemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms

This file is a modified version of Google's FunctionGemma (google/functiongemma-270m-it): fine-tuned on Prevon's data (see the Prevon Pulse card) and then converted and quantized to GGUF Q8_0. It is a Model Derivative under the Gemma Terms of Use, which apply in full; Prevon adds a short set of terms on top (see License).

Superseded

Newer builds: Prevon Pulse MK4 and MK2, each with a GGUF.

Use and limits

Built for the Prevon app's own prompt format; it is not a general chat model. Use is subject to the Gemma Terms of Use and Prohibited Use Policy (https://ai.google.dev/gemma/terms, https://ai.google.dev/gemma/prohibited_use_policy).

License

Gemma Terms of Use (ai.google.dev/gemma/terms) and Prohibited Use Policy (ai.google.dev/gemma/prohibited_use_policy) apply in full. Prevon adds a short set of terms: see PREVON_MODEL_TERMS.md. Short version: free for people, schools, researchers and non-profits; companies and anything that makes money need Prevon's written permission; competitors are never covered; rename it if you change it.

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GGUF

Model size

0.3B params

Architecture

gemma3

Hardware compatibility

8-bit

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