Instructions to use mlx-community/Falcon-H1-Tiny-R-0.6B-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Falcon-H1-Tiny-R-0.6B-8bit 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/Falcon-H1-Tiny-R-0.6B-8bit") 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/Falcon-H1-Tiny-R-0.6B-8bit 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/Falcon-H1-Tiny-R-0.6B-8bit"
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/Falcon-H1-Tiny-R-0.6B-8bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use mlx-community/Falcon-H1-Tiny-R-0.6B-8bit 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/Falcon-H1-Tiny-R-0.6B-8bit"
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/Falcon-H1-Tiny-R-0.6B-8bit
Run Hermes
hermes
- MLX LM
How to use mlx-community/Falcon-H1-Tiny-R-0.6B-8bit 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/Falcon-H1-Tiny-R-0.6B-8bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "mlx-community/Falcon-H1-Tiny-R-0.6B-8bit" # 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/Falcon-H1-Tiny-R-0.6B-8bit", "messages": [ {"role": "user", "content": "Hello"} ] }'
| {%- if tools %} {{bos_token}}<|system|> | |
| {%- if messages[0]['role'] == 'system' %} | |
| {{ messages[0]['content'] }} | |
| {%- set remaining_messages = messages[1:] %} | |
| {%- else %} | |
| {%- set remaining_messages = messages %} | |
| {%- endif %} | |
| {{ 'You are a Falcon assistant skilled in function calling. You are helpful, respectful, and concise. | |
| # Tools | |
| You have access to the following functions. You MUST use them to answer questions when needed. For each function call, you MUST return a JSON object inside <tool_call></tool_call> tags. | |
| <tools>' + tools|tojson(indent=2) + '</tools> | |
| # Output Format | |
| Your response MUST follow this format when making function calls: | |
| <tool_call> | |
| [ | |
| {"name": "function_name", "arguments": {"arg1": "value1", "arg2": "value2"}}, | |
| {"name": "another_function", "arguments": {"arg": "value"}} | |
| ] | |
| </tool_call> | |
| If no function calls are needed, respond normally without the tool_call tags.' }} | |
| {%- for message in remaining_messages %} | |
| {%- if message['role'] == 'user' %} | |
| <|im_start|>user | |
| {{ message['content'] }}<|im_end|> | |
| {%- elif message['role'] == 'assistant' %} | |
| {%- if message.content %} | |
| <|im_start|>assistant | |
| {{ message['content'] }} | |
| <|im_end|> | |
| {%- endif %} | |
| {%- if message.tool_calls %} | |
| <tool_call> | |
| {{ message.tool_calls|tojson(indent=2) }} | |
| </tool_call> | |
| {%- endif %} | |
| {%- elif message['role'] == 'tool' %} | |
| <|im_start|>assistant | |
| <tool_response> | |
| {{ message['content'] }} | |
| </tool_response><|im_end|> | |
| {%- endif %} | |
| {%- endfor %} | |
| {{ '<|im_start|>assistant | |
| ' if add_generation_prompt }} | |
| {%- else %} {{bos_token}}{% for message in messages %} {{ '<|im_start|>' + message['role'] + ' | |
| ' + message['content'] + '<|im_end|> | |
| ' }} {% endfor %} {% if add_generation_prompt %}{{ '<|im_start|>assistant | |
| ' }}{% endif %} {%- endif %} |