Instructions to use Theboukadida/laura-en-lfm2.5-1.2b-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 Theboukadida/laura-en-lfm2.5-1.2b-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 Theboukadida/laura-en-lfm2.5-1.2b-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Theboukadida/laura-en-lfm2.5-1.2b-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 Theboukadida/laura-en-lfm2.5-1.2b-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Theboukadida/laura-en-lfm2.5-1.2b-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 Theboukadida/laura-en-lfm2.5-1.2b-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Theboukadida/laura-en-lfm2.5-1.2b-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 Theboukadida/laura-en-lfm2.5-1.2b-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Theboukadida/laura-en-lfm2.5-1.2b-GGUF:Q4_K_M

Use Docker

docker model run hf.co/Theboukadida/laura-en-lfm2.5-1.2b-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use Theboukadida/laura-en-lfm2.5-1.2b-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Theboukadida/laura-en-lfm2.5-1.2b-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": "Theboukadida/laura-en-lfm2.5-1.2b-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Theboukadida/laura-en-lfm2.5-1.2b-GGUF:Q4_K_M

Ollama
How to use Theboukadida/laura-en-lfm2.5-1.2b-GGUF with Ollama:
```
ollama run hf.co/Theboukadida/laura-en-lfm2.5-1.2b-GGUF:Q4_K_M
```
Unsloth Desktop

How to use Theboukadida/laura-en-lfm2.5-1.2b-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Theboukadida/laura-en-lfm2.5-1.2b-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": "Theboukadida/laura-en-lfm2.5-1.2b-GGUF:Q4_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use Theboukadida/laura-en-lfm2.5-1.2b-GGUF with Docker Model Runner:
```
docker model run hf.co/Theboukadida/laura-en-lfm2.5-1.2b-GGUF:Q4_K_M
```

Lemonade

How to use Theboukadida/laura-en-lfm2.5-1.2b-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Theboukadida/laura-en-lfm2.5-1.2b-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.laura-en-lfm2.5-1.2b-GGUF-Q4_K_M

List all available models

lemonade list

Hermes Agent

How to use Theboukadida/laura-en-lfm2.5-1.2b-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 Theboukadida/laura-en-lfm2.5-1.2b-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 Theboukadida/laura-en-lfm2.5-1.2b-GGUF:Q4_K_M

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use Theboukadida/laura-en-lfm2.5-1.2b-GGUF with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf Theboukadida/laura-en-lfm2.5-1.2b-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 "Theboukadida/laura-en-lfm2.5-1.2b-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"

Theboukadida commited on 15 days ago

Commit

b5ae926

verified ·

1 Parent(s): 05552e9

Upload README.md with huggingface_hub

Browse files

Files changed (1) hide show

README.md +45 -0

README.md ADDED Viewed

	@@ -0,0 +1,45 @@

+---
+license: other
+license_name: lfm1.0
+license_link: LICENSE
+base_model: LiquidAI/LFM2.5-1.2B-Instruct
+language:
+- de
+- en
+pipeline_tag: text-generation
+tags:
+- gguf
+- lfm2
+- german
+- language-learning
+- on-device
+---
+# Laura — German tutor in English (LFM2.5 1.2B, GGUF)
+Laura is the tutor in an offline German course app for adult beginners
+(A1–A2). This model talks to the learner in English and teaches German with
+German examples. It runs on the phone, CPU only.
+**This is a modified version of [LiquidAI/LFM2.5-1.2B-Instruct](https://huggingface.co/LiquidAI/LFM2.5-1.2B-Instruct).**
+Changes made: a LoRA adapter (rank 16, all linear layers, 2 epochs) was trained
+on ~2,500–3,300 short tutoring conversations in English, merged into the weights,
+and the result converted to GGUF and quantised to Q4_K_M with llama.cpp.
+Distributed under the base model's LFM Open License v1.0 — see [LICENSE](LICENSE).
+## How the app uses it
+The app does not trust the model to judge German on its own. It checks the
+learner's sentence with its own dictionary first and adds the verdict to the
+message — `(Check: ✗ → „corrected sentence“ · reason)` or `(Check: ✓ …)` — plus
+dictionary meanings and the chapter's rule card. The model was trained with
+exactly those notes and explains them; without them it is a much weaker teacher.
+## Evaluation
+Hand-graded on held-out conversations it never saw in training: correct
+teaching in 80% of replies (every German fact and reason right).
+## Files
+- `laura-en-lfm2.5-1.2b-Q4_K_M.gguf` — Q4_K_M, 0.73 GB