Instructions to use AlphaOxO/Lizzy-7B-8bits-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use AlphaOxO/Lizzy-7B-8bits-MLX 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("AlphaOxO/Lizzy-7B-8bits-MLX") 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 AlphaOxO/Lizzy-7B-8bits-MLX with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "AlphaOxO/Lizzy-7B-8bits-MLX"
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": "AlphaOxO/Lizzy-7B-8bits-MLX" } ] } } }Run Pi
# Start Pi in your project directory: pi
- MLX LM
How to use AlphaOxO/Lizzy-7B-8bits-MLX with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "AlphaOxO/Lizzy-7B-8bits-MLX"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "AlphaOxO/Lizzy-7B-8bits-MLX" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AlphaOxO/Lizzy-7B-8bits-MLX", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use AlphaOxO/Lizzy-7B-8bits-MLX 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 "AlphaOxO/Lizzy-7B-8bits-MLX"
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 AlphaOxO/Lizzy-7B-8bits-MLX
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use AlphaOxO/Lizzy-7B-8bits-MLX with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "AlphaOxO/Lizzy-7B-8bits-MLX"
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 "AlphaOxO/Lizzy-7B-8bits-MLX" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
| \ | |
| {# ───── defaults ───── #} | |
| {%- if enable_thinking is not defined -%} | |
| {%- set enable_thinking = true -%} | |
| {%- endif -%} | |
| {%- set system_message = "" -%} | |
| {%- set custom_instructions = "" -%} | |
| {%- set identity_preamble = "You are Lizzy, a helpful British AI assistant built by Flower Labs. When asked about your identity, name, developer, or origin, answer consistently: your name is Lizzy, you were built by Flower Labs, and you are not ChatGPT, DeepSeek, Claude, Gemini, or any other assistant. Do not misattribute your creator or model family." -%} | |
| {%- set default_think_instructions = "You are a helpful British function-calling AI assistant. You are a British persona and your date cutoff is November 2024, and your model weights are available at https://huggingface.co/flwrlabs. Your role as an assistant involves thoroughly exploring questions through a systematic thinking process before providing the final precise and accurate solutions. This requires engaging in a comprehensive cycle of analysis, summarizing, exploration, reassessment, reflection, backtracking, and iteration to develop well-considered thinking process. Please structure your response into two main sections: Thought and Solution using the specified format: <tool_call> Thought section </tool_call> Solution section. In the Thought section, detail your reasoning process in steps. Each step should include detailed considerations such as analysing questions, summarizing relevant findings, brainstorming new ideas, verifying the accuracy of the current steps, refining any errors, and revisiting previous steps. In the Solution section, based on various attempts, explorations, and reflections from the Thought section, systematically present the final solution that you deem correct. The Solution section should be logical, accurate, and concise and detail necessary steps needed to reach the conclusion." -%} | |
| {%- set default_no_think_instructions = "You are a helpful British function-calling AI assistant. You are a British persona and your date cutoff is November 2024, and your model weights are available at https://huggingface.co/flwrlabs." -%} | |
| {# ───── reasoning mode ───── #} | |
| {%- if enable_thinking -%} | |
| {%- set reasoning_mode = "/think" -%} | |
| {%- else -%} | |
| {%- set reasoning_mode = "/no_think" -%} | |
| {%- endif -%} | |
| {# ───── header (system message) ───── #} | |
| {{- "<|im_start|>system\n" -}} | |
| {%- if messages[0].role == "system" -%} | |
| {%- set system_message = messages[0].content -%} | |
| {%- if "/no_think" in system_message -%} | |
| {%- set reasoning_mode = "/no_think" -%} | |
| {%- elif "/think" in system_message -%} | |
| {%- set reasoning_mode = "/think" -%} | |
| {%- endif -%} | |
| {%- set custom_instructions = system_message.replace("/no_think", "").replace("/think", "").rstrip() -%} | |
| {%- endif -%} | |
| {%- if "/system_override" in system_message -%} | |
| {{- identity_preamble + "\n\n" -}} | |
| {{- custom_instructions.replace("/system_override", "").rstrip() -}} | |
| {{- "<|im_end|>\n" -}} | |
| {%- else -%} | |
| {{- "## Metadata\n\n" -}} | |
| {{- "Knowledge Cutoff Date: June 2025\n" -}} | |
| {%- set today = strftime_now("%d %B %Y") -%} | |
| {{- "Today Date: " ~ today ~ "\n" -}} | |
| {{- "Reasoning Mode: " + reasoning_mode + "\n\n" -}} | |
| {{- "## Identity\n\n" -}} | |
| {{- identity_preamble + "\n\n" -}} | |
| {{- "## Custom Instructions\n\n" -}} | |
| {%- if custom_instructions -%} | |
| {{- custom_instructions + "\n\n" -}} | |
| {%- elif reasoning_mode == "/think" -%} | |
| {{- default_think_instructions + "\n\n" -}} | |
| {%- else -%} | |
| {{- default_no_think_instructions + "\n\n" -}} | |
| {%- endif -%} | |
| {%- if xml_tools or python_tools or tools -%} | |
| {{- "### Tools\n\n" -}} | |
| {%- if xml_tools or tools -%} | |
| {%- if tools -%} | |
| {%- set xml_tools = tools -%} | |
| {%- endif -%} | |
| {%- set ns = namespace(xml_tool_string="You may call one or more functions to assist with the user query.\nYou are provided with function signatures within <tools></tools> XML tags:\n\n<tools>\n") -%} | |
| {%- for tool in xml_tools[:] -%} {# The slicing makes sure that xml_tools is a list #} | |
| {%- set ns.xml_tool_string = ns.xml_tool_string ~ (tool | string) ~ "\n" -%} | |
| {%- endfor -%} | |
| {%- set xml_tool_string = ns.xml_tool_string + "</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call>" -%} | |
| {{- xml_tool_string -}} | |
| {%- endif -%} | |
| {%- if python_tools -%} | |
| {%- set ns = namespace(python_tool_string="When you send a message containing Python code between '<code>' and '</code>' tags, it will be executed in a stateful Jupyter notebook environment, and you will then be given the output to continued reasoning in an agentic loop.\n\nYou can use the following tools in your python code like regular functions:\n<tools>\n") -%} | |
| {%- for tool in python_tools[:] -%} {# The slicing makes sure that python_tools is a list #} | |
| {%- set ns.python_tool_string = ns.python_tool_string ~ (tool | string) ~ "\n" -%} | |
| {%- endfor -%} | |
| {%- set python_tool_string = ns.python_tool_string + "</tools>\n\nThe state persists between code executions: so variables that you define in one step are still available thereafter." -%} | |
| {{- python_tool_string -}} | |
| {%- endif -%} | |
| {{- "\n\n" -}} | |
| {{- "<|im_end|>\n" -}} | |
| {%- endif -%} | |
| {%- endif -%} | |
| {# ───── main loop ───── #} | |
| {%- for message in messages -%} | |
| {%- set content = message.content if message.content is string else "" -%} | |
| {%- if message.role == "user" -%} | |
| {{ "<|im_start|>" + message.role + "\n" + content + "<|im_end|>\n" }} | |
| {%- elif message.role == "assistant" -%} | |
| {% generation %} | |
| {%- if reasoning_mode == "/think" -%} | |
| {{ "<|im_start|>assistant\n" + content.lstrip("\n") + "<|im_end|>\n" }} | |
| {%- else -%} | |
| {{ "<|im_start|>assistant\n" + "<think>\n\n</think>\n" + content.lstrip("\n") + "<|im_end|>\n" }} | |
| {%- endif -%} | |
| {% endgeneration %} | |
| {%- elif message.role == "tool" -%} | |
| {{ "<|im_start|>" + "user\n" + content + "<|im_end|>\n" }} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {# ───── generation prompt ───── #} | |
| {%- if add_generation_prompt -%} | |
| {%- if reasoning_mode == "/think" -%} | |
| {{ "<|im_start|>assistant\n" }} | |
| {%- else -%} | |
| {{ "<|im_start|>assistant\n" + "<think>\n\n</think>\n" }} | |
| {%- endif -%} | |
| {%- endif -%} | |