Instructions to use LiquidAI/LFM2-2.6B-Exp-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use LiquidAI/LFM2-2.6B-Exp-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/LFM2-2.6B-Exp-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf LiquidAI/LFM2-2.6B-Exp-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/LFM2-2.6B-Exp-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf LiquidAI/LFM2-2.6B-Exp-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/LFM2-2.6B-Exp-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf LiquidAI/LFM2-2.6B-Exp-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/LFM2-2.6B-Exp-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf LiquidAI/LFM2-2.6B-Exp-GGUF:Q4_K_M

Use Docker

docker model run hf.co/LiquidAI/LFM2-2.6B-Exp-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use LiquidAI/LFM2-2.6B-Exp-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LiquidAI/LFM2-2.6B-Exp-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/LFM2-2.6B-Exp-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/LiquidAI/LFM2-2.6B-Exp-GGUF:Q4_K_M

Ollama
How to use LiquidAI/LFM2-2.6B-Exp-GGUF with Ollama:
```
ollama run hf.co/LiquidAI/LFM2-2.6B-Exp-GGUF:Q4_K_M
```

Unsloth Studio

How to use LiquidAI/LFM2-2.6B-Exp-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/LFM2-2.6B-Exp-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/LFM2-2.6B-Exp-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/LFM2-2.6B-Exp-GGUF to start chatting

How to use LiquidAI/LFM2-2.6B-Exp-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf LiquidAI/LFM2-2.6B-Exp-GGUF:Q4_K_M

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/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/LFM2-2.6B-Exp-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use LiquidAI/LFM2-2.6B-Exp-GGUF with Docker Model Runner:
```
docker model run hf.co/LiquidAI/LFM2-2.6B-Exp-GGUF:Q4_K_M
```

Lemonade

How to use LiquidAI/LFM2-2.6B-Exp-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull LiquidAI/LFM2-2.6B-Exp-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.LFM2-2.6B-Exp-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use LiquidAI/LFM2-2.6B-Exp-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 LiquidAI/LFM2-2.6B-Exp-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/LFM2-2.6B-Exp-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use LiquidAI/LFM2-2.6B-Exp-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf LiquidAI/LFM2-2.6B-Exp-GGUF:Q4_K_M

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 "LiquidAI/LFM2-2.6B-Exp-GGUF:Q4_K_M" \
  --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"

Tarek Dakhran commited on Dec 25, 2025

Commit

bafbe0c

verified ·

1 Parent(s): 61b38de

Update README.md

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README.md +40 -1

README.md CHANGED Viewed

@@ -1,12 +1,51 @@
 ---
 license: other
 license_name: lfm1.0
 license_link: LICENSE
 tags:
 - liquid
 - lfm2
 - edge
 base_model:
 - LiquidAI/LFM2-2.6B-Exp
 ---

 ---
 license: other
 license_name: lfm1.0
 license_link: LICENSE
+language:
+- en
+- ar
+- zh
+- fr
+- de
+- ja
+- ko
+- es
+pipeline_tag: text-generation
 tags:
 - liquid
 - lfm2
 - edge
+- llama.cpp
+- gguf
 base_model:
 - LiquidAI/LFM2-2.6B-Exp
 ---
+<center>
+<div style="text-align: center;">
+  <img
+    src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/2b08LKpev0DNEk6DlnWkY.png"
+    alt="Liquid AI"
+    style="width: 100%; max-width: 100%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em;"
+  />
+</div>
+<div style="display: flex; justify-content: center; gap: 0.5em;">
+  <a href="https://playground.liquid.ai/chat">
+<a href="https://playground.liquid.ai/"><strong>Try LFM</strong></a> • <a href="https://docs.liquid.ai/lfm"><strong>Documentation</strong></a> • <a href="https://leap.liquid.ai/"><strong>LEAP</strong></a></a>
+</div>
+</center>
+# LFM2-2.6B-Exp-GGUF
+LFM2 is a new generation of hybrid models developed by [Liquid AI](https://www.liquid.ai/), specifically designed for edge AI and on-device deployment. It sets a new standard in terms of quality, speed, and memory efficiency.
+Find more details in the original model card: https://huggingface.co/LiquidAI/LFM2-2.6B-Exp
+## 🏃 How to run LFM2
+Example usage with [llama.cpp](https://github.com/ggml-org/llama.cpp):
+```
+llama-cli -hf LiquidAI/LFM2-2.6B-Exp-GGUF
+```