Instructions to use bearzi/gemma-4-E4B-it-oQ2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use bearzi/gemma-4-E4B-it-oQ2 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("bearzi/gemma-4-E4B-it-oQ2") 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
- LM Studio
- Pi new
How to use bearzi/gemma-4-E4B-it-oQ2 with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "bearzi/gemma-4-E4B-it-oQ2"
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": "bearzi/gemma-4-E4B-it-oQ2" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use bearzi/gemma-4-E4B-it-oQ2 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 "bearzi/gemma-4-E4B-it-oQ2"
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 bearzi/gemma-4-E4B-it-oQ2
Run Hermes
hermes
- MLX LM
How to use bearzi/gemma-4-E4B-it-oQ2 with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "bearzi/gemma-4-E4B-it-oQ2"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "bearzi/gemma-4-E4B-it-oQ2" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bearzi/gemma-4-E4B-it-oQ2", "messages": [ {"role": "user", "content": "Hello"} ] }'
| { | |
| "audio_token": "<|audio|>", | |
| "backend": "tokenizers", | |
| "boa_token": "<|audio>", | |
| "boi_token": "<|image>", | |
| "bos_token": "<bos>", | |
| "eoa_token": "<audio|>", | |
| "eoc_token": "<channel|>", | |
| "eoi_token": "<image|>", | |
| "eos_token": "<eos>", | |
| "eot_token": "<turn|>", | |
| "escape_token": "<|\"|>", | |
| "etc_token": "<tool_call|>", | |
| "etd_token": "<tool|>", | |
| "etr_token": "<tool_response|>", | |
| "extra_special_tokens": [ | |
| "<|video|>" | |
| ], | |
| "image_token": "<|image|>", | |
| "mask_token": "<mask>", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<pad>", | |
| "padding_side": "left", | |
| "processor_class": "Gemma4Processor", | |
| "response_schema": { | |
| "type": "object", | |
| "properties": { | |
| "role": { | |
| "const": "assistant" | |
| }, | |
| "thinking": { | |
| "type": "string" | |
| }, | |
| "content": { | |
| "type": "string" | |
| }, | |
| "tool_calls": { | |
| "x-regex-iterator": "<\\|tool_call>(.*?)<tool_call\\|>", | |
| "type": "array", | |
| "items": { | |
| "type": "object", | |
| "properties": { | |
| "type": { | |
| "const": "function" | |
| }, | |
| "function": { | |
| "type": "object", | |
| "x-regex": "call\\:(?P<name>\\w+)(?P<arguments>\\{.*\\})", | |
| "properties": { | |
| "name": { | |
| "type": "string" | |
| }, | |
| "arguments": { | |
| "type": "object", | |
| "x-parser": "gemma4-tool-call", | |
| "additionalProperties": {} | |
| } | |
| } | |
| } | |
| } | |
| } | |
| } | |
| }, | |
| "x-regex": "(\\<\\|channel\\>thought\\n(?P<thinking>.*?)\\<channel\\|\\>)?(?P<tool_calls>\\<\\|tool_call\\>.*\\<tool_call\\|\\>)?(?P<content>(?:(?!\\<turn\\|\\>)(?!\\<\\|tool_response\\>).)+)?(?:\\<turn\\|\\>|\\<\\|tool_response\\>)?" | |
| }, | |
| "soc_token": "<|channel>", | |
| "sot_token": "<|turn>", | |
| "stc_token": "<|tool_call>", | |
| "std_token": "<|tool>", | |
| "str_token": "<|tool_response>", | |
| "think_token": "<|think|>", | |
| "tokenizer_class": "GemmaTokenizer", | |
| "unk_token": "<unk>" | |
| } | |