Instructions to use mudler/LFM2.5-8B-A1B-APEX-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use mudler/LFM2.5-8B-A1B-APEX-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf mudler/LFM2.5-8B-A1B-APEX-GGUF # Run inference directly in the terminal: llama cli -hf mudler/LFM2.5-8B-A1B-APEX-GGUF
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf mudler/LFM2.5-8B-A1B-APEX-GGUF # Run inference directly in the terminal: llama cli -hf mudler/LFM2.5-8B-A1B-APEX-GGUF
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf mudler/LFM2.5-8B-A1B-APEX-GGUF # Run inference directly in the terminal: ./llama-cli -hf mudler/LFM2.5-8B-A1B-APEX-GGUF
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf mudler/LFM2.5-8B-A1B-APEX-GGUF # Run inference directly in the terminal: ./build/bin/llama-cli -hf mudler/LFM2.5-8B-A1B-APEX-GGUF
Use Docker
docker model run hf.co/mudler/LFM2.5-8B-A1B-APEX-GGUF
- LM Studio
- Jan
- Ollama
How to use mudler/LFM2.5-8B-A1B-APEX-GGUF with Ollama:
ollama run hf.co/mudler/LFM2.5-8B-A1B-APEX-GGUF
- Unsloth Studio
How to use mudler/LFM2.5-8B-A1B-APEX-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for mudler/LFM2.5-8B-A1B-APEX-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for mudler/LFM2.5-8B-A1B-APEX-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for mudler/LFM2.5-8B-A1B-APEX-GGUF to start chatting
- Pi
How to use mudler/LFM2.5-8B-A1B-APEX-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf mudler/LFM2.5-8B-A1B-APEX-GGUF
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "mudler/LFM2.5-8B-A1B-APEX-GGUF" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use mudler/LFM2.5-8B-A1B-APEX-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf mudler/LFM2.5-8B-A1B-APEX-GGUF
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 mudler/LFM2.5-8B-A1B-APEX-GGUF
Run Hermes
hermes
- OpenClaw new
How to use mudler/LFM2.5-8B-A1B-APEX-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf mudler/LFM2.5-8B-A1B-APEX-GGUF
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 "mudler/LFM2.5-8B-A1B-APEX-GGUF" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
- Docker Model Runner
How to use mudler/LFM2.5-8B-A1B-APEX-GGUF with Docker Model Runner:
docker model run hf.co/mudler/LFM2.5-8B-A1B-APEX-GGUF
- Lemonade
How to use mudler/LFM2.5-8B-A1B-APEX-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mudler/LFM2.5-8B-A1B-APEX-GGUF
Run and chat with the model
lemonade run user.LFM2.5-8B-A1B-APEX-GGUF-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
Update the chat_template
#1
by abhinand - opened
The LFM team made a fix recently for the broken tool calls. Can you please update the template? Here's the correct jinja file:
{{- 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 -%}
I lost this somehow in my notifications - doing it now!
Quants updated.
mudler changed discussion status to closed