Instructions to use LiquidAI/LFM2-350M-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 LiquidAI/LFM2-350M-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 LiquidAI/LFM2-350M-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf LiquidAI/LFM2-350M-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf LiquidAI/LFM2-350M-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf LiquidAI/LFM2-350M-GGUF:Q4_K_M
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 LiquidAI/LFM2-350M-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf LiquidAI/LFM2-350M-GGUF:Q4_K_M
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 LiquidAI/LFM2-350M-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf LiquidAI/LFM2-350M-GGUF:Q4_K_M
Use Docker
docker model run hf.co/LiquidAI/LFM2-350M-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use LiquidAI/LFM2-350M-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "LiquidAI/LFM2-350M-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LiquidAI/LFM2-350M-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/LiquidAI/LFM2-350M-GGUF:Q4_K_M
- Ollama
How to use LiquidAI/LFM2-350M-GGUF with Ollama:
ollama run hf.co/LiquidAI/LFM2-350M-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use LiquidAI/LFM2-350M-GGUF with Docker Model Runner:
docker model run hf.co/LiquidAI/LFM2-350M-GGUF:Q4_K_M
- Lemonade
How to use LiquidAI/LFM2-350M-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull LiquidAI/LFM2-350M-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.LFM2-350M-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
| { | |
| "inference_type": "llama.cpp/text-to-text", | |
| "schema_version": "1.0.0", | |
| "load_time_parameters": { | |
| "model": "../LFM2-350M-Q8_0.gguf", | |
| "chat_template": "{{- bos_token -}}\n{%- set system_prompt = \"\" -%}\n{%- set ns = namespace(system_prompt=\"\") -%}\n{%- if messages[0][\"role\"] == \"system\" -%}\n\t{%- set ns.system_prompt = messages[0][\"content\"] -%}\n\t{%- set messages = messages[1:] -%}\n{%- endif -%}\n{%- if tools -%}\n\t{%- set ns.system_prompt = ns.system_prompt + (\"\\n\" if ns.system_prompt else \"\") + \"List of tools: <|tool_list_start|>[\" -%}\n\t{%- for tool in tools -%}\n\t\t{%- if tool is not string -%}\n\t\t\t{%- set tool = tool | tojson -%}\n\t\t{%- endif -%}\n\t\t{%- set ns.system_prompt = ns.system_prompt + tool -%}\n\t\t{%- if not loop.last -%}\n\t\t\t{%- set ns.system_prompt = ns.system_prompt + \", \" -%}\n\t\t{%- endif -%}\n\t{%- endfor -%}\n\t{%- set ns.system_prompt = ns.system_prompt + \"]<|tool_list_end|>\" -%}\n{%- endif -%}\n{%- if ns.system_prompt -%}\n\t{{- \"<|im_start|>system\\n\" + ns.system_prompt + \"<|im_end|>\\n\" -}}\n{%- endif -%}\n{%- for message in messages -%}\n\t{{- \"<|im_start|>\" + message[\"role\"] + \"\\n\" -}}\n\t{%- set content = message[\"content\"] -%}\n\t{%- if content is not string -%}\n\t\t{%- set content = content | tojson -%}\n\t{%- endif -%}\n\t{%- if message[\"role\"] == \"tool\" -%}\n\t\t{%- set content = \"<|tool_response_start|>\" + content + \"<|tool_response_end|>\" -%}\n\t{%- endif -%}\n\t{{- content + \"<|im_end|>\\n\" -}}\n{%- endfor -%}\n{%- if add_generation_prompt -%}\n\t{{- \"<|im_start|>assistant\\n\" -}}\n{%- endif -%}\n" | |
| }, | |
| "generation_time_parameters": { | |
| "sampling_parameters": { | |
| "temperature": 0.3, | |
| "min_p": 0.15, | |
| "repetition_penalty": 1.05 | |
| } | |
| } | |
| } |