Instructions to use mlx-community/gemma-4-12B-it-qat-assistant-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/gemma-4-12B-it-qat-assistant-4bit 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("mlx-community/gemma-4-12B-it-qat-assistant-4bit") 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) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use mlx-community/gemma-4-12B-it-qat-assistant-4bit with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "mlx-community/gemma-4-12B-it-qat-assistant-4bit"
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": "mlx-community/gemma-4-12B-it-qat-assistant-4bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use mlx-community/gemma-4-12B-it-qat-assistant-4bit 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 "mlx-community/gemma-4-12B-it-qat-assistant-4bit"
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 mlx-community/gemma-4-12B-it-qat-assistant-4bit
Run Hermes
hermes
- MLX LM
How to use mlx-community/gemma-4-12B-it-qat-assistant-4bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "mlx-community/gemma-4-12B-it-qat-assistant-4bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "mlx-community/gemma-4-12B-it-qat-assistant-4bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mlx-community/gemma-4-12B-it-qat-assistant-4bit", "messages": [ {"role": "user", "content": "Hello"} ] }'
gemma-4-12B-it-qat-assistant-4bit
This repository contains Multi-Token Prediction (MTP) drafter weights split from google/gemma-4-12B-it-qat-q4_0-unquantized-assistant for use with mlx-vlm speculative decoding.
This is not a standalone chat or text-generation model. Load it as the draft model alongside a compatible Gemma 4 12B target checkpoint.
Use with mlx-vlm
uv run mlx_vlm.generate \
--model google/gemma-4-12B-it \
--draft-model mlx-community/gemma-4-12B-it-qat-assistant-4bit \
--draft-kind mtp \
--prompt "Describe this image." \
--max-tokens 256
For local weights:
uv run mlx_vlm.generate \
--model /path/to/target-model \
--draft-model /path/to/gemma-4-12B-mtp \
--draft-kind mtp \
--prompt "Describe this image." \
--max-tokens 256
Model Details
- Model type:
gemma4_unified_assistant - Target architecture: Gemma 4 12B
- Precision: 4bit
- Runtime: MLX /
mlx-vlm - Format: Safetensors with MLX-compatible config and tokenizer files
The stored tensors are 4bit MLX-compatible drafter weights.
Intended Use
Use this repo only as a speculative decoding drafter for compatible Gemma 4 12B checkpoints. The target model verifies drafted tokens, while this MTP model proposes candidate tokens per decoding step.
Limitations
This checkpoint requires runtime support for Gemma 4 MTP draft models in mlx-vlm. Standard standalone generation through generic Transformers APIs is not expected to work with this repository by itself.
Please refer to the upstream google/gemma-4-12B-it model card and license terms for model usage constraints.
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Base model
google/gemma-4-12B-it-assistant