Instructions to use LiquidAI/LFM2.5-Encoder-230M-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/LFM2.5-Encoder-230M-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/LFM2.5-Encoder-230M-GGUF:F16
# Run inference directly in the terminal:
llama cli -hf LiquidAI/LFM2.5-Encoder-230M-GGUF:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf LiquidAI/LFM2.5-Encoder-230M-GGUF:F16
# Run inference directly in the terminal:
llama cli -hf LiquidAI/LFM2.5-Encoder-230M-GGUF:F16

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf LiquidAI/LFM2.5-Encoder-230M-GGUF:F16
# Run inference directly in the terminal:
./build/bin/llama cli -hf LiquidAI/LFM2.5-Encoder-230M-GGUF:F16

Use Docker

docker model run hf.co/LiquidAI/LFM2.5-Encoder-230M-GGUF:F16

Llama new
LM Studio
Jan
Ollama
How to use LiquidAI/LFM2.5-Encoder-230M-GGUF with Ollama:
```
ollama run hf.co/LiquidAI/LFM2.5-Encoder-230M-GGUF:F16
```
Unsloth Desktop

How to use LiquidAI/LFM2.5-Encoder-230M-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/LFM2.5-Encoder-230M-GGUF:F16

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/LFM2.5-Encoder-230M-GGUF:F16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use LiquidAI/LFM2.5-Encoder-230M-GGUF with Docker Model Runner:
```
docker model run hf.co/LiquidAI/LFM2.5-Encoder-230M-GGUF:F16
```

Lemonade

How to use LiquidAI/LFM2.5-Encoder-230M-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull LiquidAI/LFM2.5-Encoder-230M-GGUF:F16

Run and chat with the model

lemonade run user.LFM2.5-Encoder-230M-GGUF-F16

List all available models

lemonade list

Hermes Agent

How to use LiquidAI/LFM2.5-Encoder-230M-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/LFM2.5-Encoder-230M-GGUF:F16

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-Encoder-230M-GGUF:F16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use LiquidAI/LFM2.5-Encoder-230M-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/LFM2.5-Encoder-230M-GGUF:F16

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/LFM2.5-Encoder-230M-GGUF:F16" \
  --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"

tuliren commited on Jul 28

Commit

125bf90

verified ·

1 Parent(s): 344a547

Add GGUF model card

Browse files

Files changed (1) hide show

README.md +52 -0

README.md ADDED Viewed

	@@ -0,0 +1,52 @@

+---
+library_name: gguf
+license: other
+license_name: lfm1.0
+license_link: LICENSE
+language:
+- en
+- ar
+- zh
+- fr
+- de
+- ja
+- ko
+- es
+- pt
+- it
+pipeline_tag: text-generation
+base_model: LiquidAI/LFM2.5-Encoder-230M
+tags:
+- liquid
+- lfm2.5
+- gguf
+- llama.cpp
+---
+<div 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 style="display: flex; justify-content: center; gap: 0.5em; margin-bottom: 1em;">
+    <a href="https://playground.liquid.ai/"><strong>Try LFM</strong></a> •
+    <a href="https://docs.liquid.ai/lfm/getting-started/welcome"><strong>Docs</strong></a> •
+    <a href="https://leap.liquid.ai/"><strong>LEAP</strong></a> •
+    <a href="https://discord.com/invite/liquid-ai"><strong>Discord</strong></a>
+  </div>
+</div>
+# LFM2.5-Encoder-230M-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/LFM2.5-Encoder-230M
+## 🏃 How to run LFM2
+Example usage with [llama.cpp](https://github.com/ggml-org/llama.cpp):
+```
+llama-cli -hf LiquidAI/LFM2.5-Encoder-230M-GGUF
+```