Instructions to use LiquidAI/LFM2-350M-PII-Extract-JP-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use LiquidAI/LFM2-350M-PII-Extract-JP-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="LiquidAI/LFM2-350M-PII-Extract-JP-GGUF",
	filename="LFM2-350M-PII-Extract-JP-F16.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use LiquidAI/LFM2-350M-PII-Extract-JP-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/LFM2-350M-PII-Extract-JP-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf LiquidAI/LFM2-350M-PII-Extract-JP-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/LFM2-350M-PII-Extract-JP-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf LiquidAI/LFM2-350M-PII-Extract-JP-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-PII-Extract-JP-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf LiquidAI/LFM2-350M-PII-Extract-JP-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-PII-Extract-JP-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf LiquidAI/LFM2-350M-PII-Extract-JP-GGUF:Q4_K_M

Use Docker

docker model run hf.co/LiquidAI/LFM2-350M-PII-Extract-JP-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use LiquidAI/LFM2-350M-PII-Extract-JP-GGUF with Ollama:
```
ollama run hf.co/LiquidAI/LFM2-350M-PII-Extract-JP-GGUF:Q4_K_M
```

Unsloth Studio new

How to use LiquidAI/LFM2-350M-PII-Extract-JP-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/LFM2-350M-PII-Extract-JP-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/LFM2-350M-PII-Extract-JP-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/LFM2-350M-PII-Extract-JP-GGUF to start chatting

Pi new

How to use LiquidAI/LFM2-350M-PII-Extract-JP-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/LFM2-350M-PII-Extract-JP-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/LFM2-350M-PII-Extract-JP-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use LiquidAI/LFM2-350M-PII-Extract-JP-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/LFM2-350M-PII-Extract-JP-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/LFM2-350M-PII-Extract-JP-GGUF:Q4_K_M

Run Hermes

hermes

Docker Model Runner
How to use LiquidAI/LFM2-350M-PII-Extract-JP-GGUF with Docker Model Runner:
```
docker model run hf.co/LiquidAI/LFM2-350M-PII-Extract-JP-GGUF:Q4_K_M
```

Lemonade

How to use LiquidAI/LFM2-350M-PII-Extract-JP-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull LiquidAI/LFM2-350M-PII-Extract-JP-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.LFM2-350M-PII-Extract-JP-GGUF-Q4_K_M

List all available models

lemonade list

Try LFM • Documentation • LEAP

LFM2-350M-PII-Extract-JP-GGUF

Based on LFM2-350M, this checkpoint is designed to extract personally identifiable information (PII) from Japanese text and output it in JSON format. The output can then be used to mask out sensitive information in contracts, emails, personal medical reports, insurance bills, etc. directly on-device.

Find more details in the original model card: https://huggingface.co/LiquidAI/LFM2-350M-PII-Extract-JP

🏃 How to run LFM2

Example usage with llama.cpp:

Extract address, company/institution names, email addresses, human names, and phone numbers from Japanese text.
```
llama-cli -hf LiquidAI/LFM2-350M-PII-Extract-JP-GGUF -st --temp 0.0 --json-schema {} --jinja
```
Specifying a particular quantization scheme (e.g. Q8_0):
```
llama-cli -hf LiquidAI/LFM2-350M-PII-Extract-JP-GGUF:Q8_0 -st --temp 0.0 --json-schema {} --jinja
```
Several quantization variants are available (Q4_0, Q4_K_M, Q5_K_M, Q6_K, Q8_0, and F16).

Only extracting particular entities (e.g. only extract address and company_name):

llama-cli -hf LiquidAI/LFM2-350M-PII-Extract-JP-GGUF -st --temp 0.0 --json-schema {} -sys "Extract <address>, <company_name>"

Downloads last month: 302

GGUF

Model size

0.4B params

Architecture

lfm2

Hardware compatibility

4-bit

5-bit

6-bit

8-bit

16-bit

Inference Providers NEW

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Model tree for LiquidAI/LFM2-350M-PII-Extract-JP-GGUF

Base model

LiquidAI/LFM2-350M

Finetuned

LiquidAI/LFM2-350M-PII-Extract-JP

Quantized

(4)

this model

Collection including LiquidAI/LFM2-350M-PII-Extract-JP-GGUF

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Collection

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