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

Libraries

How to use LiquidAI/LFM2-2.6B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="LiquidAI/LFM2-2.6B-GGUF",
	filename="LFM2-2.6B-F16.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

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

Use Docker

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

LM Studio
Jan

vLLM

How to use LiquidAI/LFM2-2.6B-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-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-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

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

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

Unsloth Studio new

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

Pi new

How to use LiquidAI/LFM2-2.6B-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/LFM2-2.6B-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/LFM2-2.6B-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

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

Run Hermes

hermes

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

Lemonade

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

Pull the model

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

Run and chat with the model

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

List all available models

lemonade list

mlabonne commited on Sep 24, 2025

Commit

ce4d10d

verified ·

1 Parent(s): e26362d

Update README.md

Browse files

Files changed (1) hide show

README.md +62 -1

README.md CHANGED Viewed

@@ -1,12 +1,73 @@
 ---
 license: other
 license_name: lfm1.0
 license_link: LICENSE
 tags:
 - liquid
 - lfm2
 - edge
 base_model:
 - LiquidAI/LFM2-2.6B
 ---

 ---
 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
 ---
+<center>
+<div style="text-align: center;">
+  <img
+    src="https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/7_6D7rWrLxp2hb6OHSV1p.png"
+    alt="Liquid AI"
+    style="width: 100%; max-width: 66%; height: auto; display: inline-block; margin-bottom: 0.5em; margin-top: 0.5em;"
+  />
+</div>
+<a href="https://playground.liquid.ai/chat">
+<svg width="114.8" height="20" viewBox="0 0 1300 200" xmlns="http://www.w3.org/2000/svg" role="img" aria-label="Liquid Playground" style="margin-bottom: 1em;">
+  <title>Liquid: Playground</title>
+  <g>
+    <rect fill="#fff" width="600" height="200"></rect>
+    <rect fill="url(#x)" x="600" width="700" height="200"></rect>
+  </g>
+  <g transform="translate(20, 30) scale(0.4, 0.4)">
+    <path d="M172.314 129.313L172.219 129.367L206.125 188.18C210.671 195.154 213.324 203.457 213.324 212.382C213.324 220.834 210.956 228.739 206.839 235.479L275.924 213.178L167.853 33.6L141.827 76.9614L172.314 129.313Z" fill="black"/>
+    <path d="M114.217 302.4L168.492 257.003C168.447 257.003 168.397 257.003 168.352 257.003C143.515 257.003 123.385 237.027 123.385 212.387C123.385 203.487 126.023 195.204 130.55 188.24L162.621 132.503L135.966 86.7327L60.0762 213.183L114.127 302.4H114.217Z" fill="black"/>
+    <path d="M191.435 250.681C191.435 250.681 191.43 250.681 191.425 250.686L129.71 302.4H221.294L267.71 226.593L191.435 250.686V250.681Z" fill="black"/>
+  </g>
+  <g aria-hidden="true" fill="#fff" text-anchor="start" font-family="Verdana,DejaVu Sans,sans-serif" font-size="110">
+    <text x="200" y="148" textLength="329" fill="#000" opacity="0.1">Liquid</text>
+    <text x="190" y="138" textLength="329" fill="#000">Liquid</text>
+    <text x="655" y="148" textLength="619" fill="#000" opacity="0.1">Playground</text>
+    <text x="645" y="138" textLength="619">Playground</text>
+  </g>
+  <linearGradient id="x" x1="0%" y1="0%" x2="100%" y2="0%">
+    <stop offset="0%" style="stop-color:#000000"></stop>
+    <stop offset="100%" style="stop-color:#000000"></stop>
+  </linearGradient>
+</svg>
+</a>
+</center>
+# LFM2-2.6B-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
+## 🏃 How to run LFM2
+Example usage with [llama.cpp](https://github.com/ggml-org/llama.cpp):
+```
+llama-cli -hf LiquidAI/LFM2-2.6B-GGUF
+```