Instructions to use sabeshbesh/LFM2.5-230M-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use sabeshbesh/LFM2.5-230M-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("sabeshbesh/LFM2.5-230M-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 sabeshbesh/LFM2.5-230M-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 "sabeshbesh/LFM2.5-230M-MLX"
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "sabeshbesh/LFM2.5-230M-MLX" } ] } } }Run Pi
# Start Pi in your project directory: pi
- MLX LM
How to use sabeshbesh/LFM2.5-230M-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 "sabeshbesh/LFM2.5-230M-MLX"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "sabeshbesh/LFM2.5-230M-MLX" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "sabeshbesh/LFM2.5-230M-MLX", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use sabeshbesh/LFM2.5-230M-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 "sabeshbesh/LFM2.5-230M-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 sabeshbesh/LFM2.5-230M-MLX
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use sabeshbesh/LFM2.5-230M-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 "sabeshbesh/LFM2.5-230M-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 "sabeshbesh/LFM2.5-230M-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"
File size: 4,621 Bytes
442cfce | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 | {{- bos_token -}}
{%- set preserve_thinking = preserve_thinking | default(false) -%}
{%- macro format_arg_value(arg_value) -%}
{%- if arg_value is string -%}
{{- "'" + arg_value + "'" -}}
{%- elif arg_value is mapping -%}
{{- arg_value | tojson -}}
{%- else -%}
{{- arg_value | string -}}
{%- endif -%}
{%- endmacro -%}
{%- macro parse_content(content) -%}
{%- if content is string -%}
{{- content -}}
{%- else -%}
{%- set _ns = namespace(result="") -%}
{%- for item in content -%}
{%- if item["type"] == "image" -%}
{%- set _ns.result = _ns.result + "<image>" -%}
{%- elif item["type"] == "text" -%}
{%- set _ns.result = _ns.result + item["text"] -%}
{%- else -%}
{%- set _ns.result = _ns.result + item | tojson -%}
{%- endif -%}
{%- endfor -%}
{{- _ns.result -}}
{%- endif -%}
{%- endmacro -%}
{%- macro render_tool_calls(tool_calls) -%}
{%- set tool_calls_ns = namespace(tool_calls=[]) -%}
{%- for tool_call in tool_calls -%}
{%- set func_name = tool_call["function"]["name"] -%}
{%- set func_args = tool_call["function"]["arguments"] -%}
{%- set args_ns = namespace(arg_strings=[]) -%}
{%- for arg_name, arg_value in func_args.items() -%}
{%- set args_ns.arg_strings = args_ns.arg_strings + [arg_name + "=" + format_arg_value(arg_value)] -%}
{%- endfor -%}
{%- set tool_calls_ns.tool_calls = tool_calls_ns.tool_calls + [func_name + "(" + (args_ns.arg_strings | join(", ")) + ")"] -%}
{%- endfor -%}
{{- "<|tool_call_start|>[" + (tool_calls_ns.tool_calls | join(", ")) + "]<|tool_call_end|>" -}}
{%- endmacro -%}
{%- set ns = namespace(system_prompt="", last_user_index=-1) -%}
{%- if messages[0]["role"] == "system" -%}
{%- if messages[0].get("content") -%}
{%- set ns.system_prompt = parse_content(messages[0]["content"]) -%}
{%- endif -%}
{%- set messages = messages[1:] -%}
{%- endif -%}
{%- if tools -%}
{%- set ns.system_prompt = ns.system_prompt + ("\n" if ns.system_prompt else "") + "List of tools: [" -%}
{%- for tool in tools -%}
{%- if tool is not string -%}
{%- set tool = tool | tojson -%}
{%- endif -%}
{%- set ns.system_prompt = ns.system_prompt + tool -%}
{%- if not loop.last -%}
{%- set ns.system_prompt = ns.system_prompt + ", " -%}
{%- endif -%}
{%- endfor -%}
{%- set ns.system_prompt = ns.system_prompt + "]" -%}
{%- endif -%}
{%- if ns.system_prompt -%}
{{- "<|im_start|>system\n" + ns.system_prompt + "<|im_end|>\n" -}}
{%- endif -%}
{%- for message in messages -%}
{%- if message["role"] == "user" -%}
{%- set ns.last_user_index = loop.index0 -%}
{%- endif -%}
{%- endfor -%}
{%- for message in messages -%}
{{- "<|im_start|>" + message.role + "\n" -}}
{%- if message.role == "assistant" -%}
{%- generation -%}
{%- if message.thinking is defined and (preserve_thinking or loop.index0 > ns.last_user_index) -%}
{{- "<think>" + message.thinking + "</think>" -}}
{%- endif -%}
{%- set _cfm_tag = "CONTINUE_FINAL_MESSAGE_TAG " -%}
{%- set _has_cfm = false -%}
{%- if message.content is defined -%}
{%- set content = parse_content(message.content) -%}
{%- if not (preserve_thinking or loop.index0 > ns.last_user_index) -%}
{%- if "</think>" in content -%}
{%- set content = content.split("</think>")[-1] | trim -%}
{%- endif -%}
{%- endif -%}
{%- if message.tool_calls is defined and content.endswith(_cfm_tag) -%}
{%- set _has_cfm = true -%}
{%- set _trunc_len = (content | length) - (_cfm_tag | length) -%}
{{- content[:_trunc_len] -}}
{%- else -%}
{{- content -}}
{%- endif -%}
{%- endif -%}
{%- if message.tool_calls is defined -%}
{{- render_tool_calls(message.tool_calls) -}}
{%- endif -%}
{%- if _has_cfm -%}
{{- _cfm_tag -}}
{%- endif -%}
{{- "<|im_end|>\n" -}}
{%- endgeneration -%}
{%- else %}
{%- if message.get("content") -%}
{{- parse_content(message["content"]) -}}
{%- endif -%}
{{- "<|im_end|>\n" -}}
{%- endif %}
{%- endfor -%}
{%- if add_generation_prompt -%}
{{- "<|im_start|>assistant\n" -}}
{%- endif -%} |