LiquidAI/LFM2.5-8B-A1B-GGUF

Hugging Face Models Trending Models

Summary

LiquidAI releases a GGUF quantized version of their LFM2.5-8B-A1B model, with instructions for use across multiple inference engines.

Task: text-generation Tags: gguf, liquid, lfm2, edge, llama.cpp, text-generation, en, ar, zh, fr, de, ja, ko, es, base_model:LiquidAI/LFM2.5-8B-A1B, base_model:quantized:LiquidAI/LFM2.5-8B-A1B, license:other, endpoints_compatible, region:us, conversational
Original Article
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Cached at: 05/29/26, 08:10 AM

LiquidAI/LFM2.5-8B-A1B-GGUF · Hugging Face

Source: https://huggingface.co/LiquidAI/LFM2.5-8B-A1B-GGUF Librariesllama-cpp-pythonHow to use LiquidAI/LFM2.5-8B-A1B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="LiquidAI/LFM2.5-8B-A1B-GGUF",
	filename="LFM2.5-8B-A1B-BF16.gguf",
)
llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

NotebooksGoogle ColabKaggleLocal Appshttps://huggingface.co/settings/local-apps#local-appsllama.cppHow to use LiquidAI/LFM2.5-8B-A1B-GGUF with llama.cpp:

Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf LiquidAI/LFM2.5-8B-A1B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf LiquidAI/LFM2.5-8B-A1B-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf LiquidAI/LFM2.5-8B-A1B-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf LiquidAI/LFM2.5-8B-A1B-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/LFM2.5-8B-A1B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf LiquidAI/LFM2.5-8B-A1B-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/LFM2.5-8B-A1B-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf LiquidAI/LFM2.5-8B-A1B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/LiquidAI/LFM2.5-8B-A1B-GGUF:Q4_K_M

LM StudioJanvLLMHow to use LiquidAI/LFM2.5-8B-A1B-GGUF with vLLM:

Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LiquidAI/LFM2.5-8B-A1B-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/LFM2.5-8B-A1B-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/LiquidAI/LFM2.5-8B-A1B-GGUF:Q4_K_M

OllamaHow to use LiquidAI/LFM2.5-8B-A1B-GGUF with Ollama:

ollama run hf.co/LiquidAI/LFM2.5-8B-A1B-GGUF:Q4_K_M

Unsloth StudionewHow to use LiquidAI/LFM2.5-8B-A1B-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 LiquidAI/LFM2.5-8B-A1B-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 LiquidAI/LFM2.5-8B-A1B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for LiquidAI/LFM2.5-8B-A1B-GGUF to start chatting

PinewHow to use LiquidAI/LFM2.5-8B-A1B-GGUF with Pi:

Start the llama.cpp server
# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf LiquidAI/LFM2.5-8B-A1B-GGUF:Q4_K_M
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": "LiquidAI/LFM2.5-8B-A1B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}
Run Pi
# Start Pi in your project directory:
pi

Hermes AgentnewHow to use LiquidAI/LFM2.5-8B-A1B-GGUF with Hermes Agent:

Start the llama.cpp server
# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf LiquidAI/LFM2.5-8B-A1B-GGUF:Q4_K_M
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 LiquidAI/LFM2.5-8B-A1B-GGUF:Q4_K_M
Run Hermes
hermes

Docker Model RunnerHow to use LiquidAI/LFM2.5-8B-A1B-GGUF with Docker Model Runner:

docker model run hf.co/LiquidAI/LFM2.5-8B-A1B-GGUF:Q4_K_M

LemonadeHow to use LiquidAI/LFM2.5-8B-A1B-GGUF with Lemonade:

Pull the model
# Download Lemonade from https://lemonade-server.ai/
lemonade pull LiquidAI/LFM2.5-8B-A1B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.LFM2.5-8B-A1B-GGUF-Q4_K_M
List all available models
lemonade list

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